WO2020047847A1 - 一种轮椅结构参数自适应调节方法、系统及存储介质 - Google Patents

一种轮椅结构参数自适应调节方法、系统及存储介质 Download PDF

Info

Publication number
WO2020047847A1
WO2020047847A1 PCT/CN2018/104626 CN2018104626W WO2020047847A1 WO 2020047847 A1 WO2020047847 A1 WO 2020047847A1 CN 2018104626 W CN2018104626 W CN 2018104626W WO 2020047847 A1 WO2020047847 A1 WO 2020047847A1
Authority
WO
WIPO (PCT)
Prior art keywords
wheelchair
parameter
environmental data
structural
data
Prior art date
Application number
PCT/CN2018/104626
Other languages
English (en)
French (fr)
Inventor
李家鑫
刘伟荣
焦寅
闫励
Original Assignee
苏州金瑞麒智能科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 苏州金瑞麒智能科技有限公司 filed Critical 苏州金瑞麒智能科技有限公司
Priority to CN201880095804.0A priority Critical patent/CN112566603B/zh
Priority to PCT/CN2018/104626 priority patent/WO2020047847A1/zh
Publication of WO2020047847A1 publication Critical patent/WO2020047847A1/zh

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
    • A61G5/00—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs
    • A61G5/04—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs motor-driven
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/72—Electric energy management in electromobility

Definitions

  • the invention relates to the technical field of intelligent wheelchairs, and more particularly, to a method, a system, and a storage medium for adaptively adjusting structural parameters of a wheelchair.
  • the existing smart wheelchair can change the movement state of the wheelchair according to the surrounding environment during driving, for example, decelerating when passing through pothole road sections.
  • the existing smart wheelchairs cannot adjust the mechanical structure parameters of the wheelchairs in real time, for example, increasing the wheelbase to increase the height of the chassis to pass through potholes. In this way, the stability and safety of the wheelchair can be improved, and at the same time, the comfort of the wheelchair user can be improved. Therefore, there is a need for a method and / or system for adjusting the mechanical structure parameters of a wheelchair according to the surrounding environment of the wheelchair to provide a better user experience.
  • some embodiments of the present invention provide a method, system, and storage medium for adaptively adjusting the structural parameters of a wheelchair.
  • the environmental data of the current scene and / or the motion data of the wheelchair and further determine the target structural parameters of the wheelchair through the current scene based on the environmental data and / or motion data, and adjust the current structural parameters of the wheelchair to achieve better stability , Safety and comfort.
  • a wheelchair structural parameter adaptive adjustment method is implemented by at least one processor, and the method may include one or more of the following operations.
  • Environment data of the current scene where the wheelchair is located and / or movement data of the wheelchair may be obtained.
  • a target structure parameter corresponding to the current scene may be determined based on the environment data and / or motion data.
  • the actuator on the wheelchair can be controlled to adjust the current structural parameter of the wheelchair to the target structural parameter.
  • the obtaining the environmental data of the current scene where the wheelchair is located and / or the movement data of the wheelchair may include at least one of the following operations.
  • the preset environment data about the current scene, or the environment data and / or the movement data of the current scene where the wheelchair is captured by one or more sensors located on the wheelchair may be acquired.
  • determining the target structure parameter corresponding to the current scene based on the environment data may include at least one of the following operations.
  • the road conditions corresponding to the current scene may be determined from the environment data; the road conditions include at least one of the following road conditions: a straight road, a curve, and a ramp.
  • a spatial parameter corresponding to the road condition may be determined.
  • a target structural parameter that passes the road condition may be determined based on the spatial parameters.
  • the spatial parameters of the road conditions include at least one of the following: straight road length, curve radius, curve arc length, slope angle, slope distance, and slope height.
  • determining the target structure parameter that passes the road condition based on the spatial parameter may include at least one of the following operations.
  • Intermediate structural parameters that pass through the road conditions may be calculated based on the spatial parameters. It can be judged whether the intermediate structure parameter exceeds the range of the structure parameter. In response to the determination that the intermediate structural parameter exceeds the range of the structural parameter, an endpoint value closer to the intermediate structural parameter in the structural parameter range is determined as the target structural parameter.
  • determining a target structure parameter that passes the road condition based on the spatial parameter may include at least one of the following operations. Intermediate structural parameters that pass through the road conditions may be calculated based on the spatial parameters. It can be judged whether the intermediate structure parameter exceeds the range of the structure parameter. In response to the determination that the intermediate structure parameter does not exceed the range of the structure parameter, the intermediate structure parameter is determined as the target structure parameter.
  • the determining a target structure parameter corresponding to the current scene based on the environment data may include at least one of the following operations.
  • a preset structure parameter corresponding to the environmental data may be acquired.
  • the preset structure parameter may be determined as the target structure parameter.
  • the structural parameters include at least one of the following: wheelbase, wheelbase, chassis height, and seat tilt.
  • the execution structure includes at least one motor for receiving a control signal of the at least one processor to perform at least one of the following operations.
  • the length of the wheelbase can be adjusted.
  • the width of the track can be adjusted.
  • the height of the chassis can be adjusted.
  • the seat tilt can be adjusted.
  • the method further includes the following operations.
  • the environmental data of the current scene and its corresponding target structure parameters may be uploaded.
  • a wheelchair structural parameter adaptive adjustment system includes at least one processor and at least one storage device, where the storage device is used to store instructions, and when the at least one processor executes the instructions, at least one of the following is implemented operating.
  • Environment data of the current scene where the wheelchair is located and / or movement data of the wheelchair may be obtained.
  • a target structure parameter corresponding to the current scene may be determined based on the environment data and / or motion data.
  • the actuator on the wheelchair can be controlled to adjust the current structural parameter of the wheelchair to the target structural parameter.
  • the processor in order to implement the acquiring environment data of the current scene where the wheelchair is located and / or movement data of the wheelchair, the processor is configured to perform at least one of the following operations.
  • the preset environment data about the current scene, or the environment data and / or the movement data of the current scene where the wheelchair is captured by one or more sensors located on the wheelchair may be acquired.
  • the processor in order to achieve the determination of a target structure parameter corresponding to the current scene based on the environment data, is used to perform at least one of the following operations.
  • the road conditions corresponding to the current scene may be determined from the environment data; the road conditions include at least one of the following road conditions: a straight road, a curve, and a ramp.
  • a spatial parameter corresponding to the road condition may be determined.
  • a target structural parameter that passes the road condition may be determined based on the spatial parameters.
  • the spatial parameters of the road conditions include at least one of the following: straight road length, curve radius, curve arc length, slope angle, slope distance, and slope height.
  • the processor in order to achieve the determination of a target structure parameter that passes the road condition based on the spatial parameter, the processor is used to perform at least one of the following operations.
  • Intermediate structural parameters that pass through the road conditions may be calculated based on the spatial parameters. It can be judged whether the intermediate structure parameter exceeds the range of the structure parameter. In response to the determination that the intermediate structural parameter exceeds the range of the structural parameter, an endpoint value closer to the intermediate structural parameter in the structural parameter range is determined as the target structural parameter.
  • the processor in order to achieve the determination of a target structure parameter that passes the road condition based on the spatial parameter, the processor is used to perform at least one of the following operations. Intermediate structural parameters that pass through the road conditions may be calculated based on the spatial parameters. It can be judged whether the intermediate structure parameter exceeds the range of the structure parameter. In response to the determination that the intermediate structure parameter does not exceed the range of the structure parameter, the intermediate structure parameter is determined as the target structure parameter.
  • the processor in order to achieve the determination of a target structure parameter corresponding to the current scene based on the environment data, is configured to perform at least one of the following operations.
  • a preset structure parameter corresponding to the environmental data may be acquired.
  • the preset structure parameter may be determined as the target structure parameter.
  • the structural parameters include at least one of the following: wheelbase, wheelbase, chassis height, and seat tilt.
  • the execution structure includes at least one motor for receiving a control signal of the at least one processor to perform at least one of the following operations.
  • the length of the wheelbase can be adjusted.
  • the width of the track can be adjusted.
  • the height of the chassis can be adjusted.
  • the seat tilt can be adjusted.
  • the processor is further configured to perform the following operations.
  • the environmental data of the current scene and its corresponding target structure parameters may be uploaded.
  • a wheelchair structural parameter adaptive adjustment system includes a first acquisition module, a first determination module, and a control module.
  • the first obtaining module is configured to obtain environmental data of a current scene where the wheelchair is located and / or movement data of the wheelchair.
  • the first determining module is configured to determine a target structure parameter corresponding to the current scene based on the environment data and / or motion data.
  • the control module is configured to control an actuator on a wheelchair to adjust a current structural parameter of the wheelchair to the target structural parameter.
  • the first acquiring module is configured to acquire preset environmental data about the current scene, or environmental data of the current scene of the wheelchair where captured by one or more sensors located on the wheelchair And / or the motion data.
  • the first determining module is configured to determine a road condition corresponding to the current scene based on the environmental data; the road condition includes at least one of the following road conditions: a straight road, a curve, and a ramp.
  • the first determining module is further configured to determine a spatial parameter corresponding to the road condition.
  • the first determining module is further configured to determine a target structure parameter that passes the road condition based on the spatial parameter.
  • the spatial parameters of the road conditions include at least one of the following: straight road length, curve radius, curve arc length, slope angle, slope distance, and slope height.
  • the first determination module in order to determine the target structural parameter that passes the road condition based on the spatial parameter, is further configured to calculate an intermediate structural parameter that passes the road condition based on the spatial parameter. Determining whether the intermediate structural parameter is outside the structural parameter range; and in response to the determination that the intermediate structural parameter is outside the structural parameter range, determining an endpoint value closer to the intermediate structural parameter in the structural parameter range as the target Structural parameters.
  • the first determination module in order to determine the target structural parameter that passes the road condition based on the spatial parameter, is further configured to calculate an intermediate structural parameter that passes the road condition based on the spatial parameter. Determining whether the intermediate structural parameter exceeds the structural parameter range; and in response to a determination that the intermediate structural parameter does not exceed the structural parameter range, determining the intermediate structural parameter as the target structural parameter.
  • the first determining module in order to determine the target structure parameter corresponding to the current scene based on the environment data, is further configured to obtain a preset structure parameter corresponding to the environment data. Determining the preset structure parameter as the target structure parameter.
  • the structural parameters include at least one of the following: wheelbase, wheelbase, chassis height, and seat tilt.
  • the execution structure includes at least one motor for receiving a control signal of the control module to perform at least one of the following operations.
  • the length of the wheelbase can be adjusted.
  • the width of the track can be adjusted.
  • the height of the chassis can be adjusted.
  • the seat tilt can be adjusted.
  • the system further includes a communication module, which is used to upload the environmental data of the current scene and its corresponding target structure parameters.
  • a computer-readable storage medium characterized in that the storage medium stores computer instructions, and when the computer reads the computer instructions in the storage medium, the computer runs the method for adaptively adjusting a wheelchair structural parameter according to any one of the above.
  • a method for adaptive adjustment of wheelchair structural parameters is implemented by at least one processor.
  • the method may include at least one of the following operations.
  • Environment data of the scene in which the wheelchair is currently located may be acquired.
  • Wheelchair structural parameters corresponding to the environmental data may be determined.
  • the wheelchair structural parameters may be sent to at least one processor on the wheelchair.
  • the method may further include at least one of the following operations. It is possible to receive and store the environmental data of the current scene in which the wheelchair is located and its corresponding wheelchair structural parameters sent to the storage device by at least one processor on the wheelchair.
  • the determining a wheelchair structure parameter corresponding to the environmental data may include at least one of the following operations.
  • a road condition corresponding to the current scene may be determined based on the environmental data; the road condition includes at least one of the following road conditions: a straight road, a curve, and a ramp.
  • a spatial parameter corresponding to the road condition may be determined. Wheelchair structural parameters that pass the road condition may be determined based on the spatial parameters.
  • the determining a wheelchair structure parameter corresponding to the environmental data may include at least one of the following operations.
  • the storage device may be queried to obtain structural parameters corresponding to the environmental data of the current scene where the wheelchair is located.
  • the storage device stores at least one set of scene-structure parameter data; the scene-structure parameter data includes environmental data of at least one scene Its corresponding wheelchair structural parameters.
  • the determining a wheelchair structure parameter corresponding to the environmental data may include at least one of the following operations.
  • the environmental data may be input into a structural parameter determination model, wherein the structural parameter determination model is a machine learning model and is obtained after training based on environmental data of multiple scenes and corresponding pairs of wheelchair structural parameter samples.
  • a model may be determined based on the structural parameters to determine the structural parameters of the wheelchair.
  • a system for adaptive adjustment of wheelchair structural parameters includes at least one processor and at least one storage device, where the storage device is used to store instructions, and when the at least one processor executes the instructions, implements Do at least one of the following.
  • Environment data of the scene in which the wheelchair is currently located may be acquired.
  • Wheelchair structural parameters corresponding to the environmental data may be determined.
  • the wheelchair structural parameters may be sent to at least one processor on the wheelchair.
  • the processor may further implement at least one of the following operations. It is possible to receive and store the environmental data of the current scene in which the wheelchair is located and its corresponding wheelchair structural parameters sent to the storage device by at least one processor on the wheelchair.
  • the processor may perform at least one of the following operations.
  • a road condition corresponding to the current scene may be determined based on the environmental data; the road condition includes at least one of the following road conditions: a straight road, a curve, and a ramp.
  • a spatial parameter corresponding to the road condition may be determined. Wheelchair structural parameters that pass the road condition may be determined based on the spatial parameters.
  • the processor may perform at least one of the following operations.
  • the storage device may be queried to obtain structural parameters corresponding to the environmental data of the current scene where the wheelchair is located.
  • the storage device stores at least one set of scene-structure parameter data; the scene-structure parameter data includes environmental data of at least one scene and Its corresponding wheelchair structural parameters.
  • the processor may perform at least one of the following operations.
  • the environmental data may be input into a structural parameter determination model, wherein the structural parameter determination model is a machine learning model and is obtained after training based on multiple scenarios and corresponding pairs of wheelchair structural parameter sample pairs.
  • a model may be determined based on the structural parameters to determine the structural parameters of the wheelchair.
  • a system for adaptive adjustment of wheelchair structural parameters includes a second acquisition module, a second determination module, and a transmission module.
  • the second acquisition module is configured to acquire environmental data of a scene in which the wheelchair is currently located.
  • the second determination module is configured to determine a wheelchair structure parameter corresponding to the environmental data.
  • the transmission module is configured to send the wheelchair structural parameters to at least one processor on the wheelchair.
  • the system may further include a receiving module for receiving and storing the environmental data of the current scene in which the wheelchair is located and the corresponding wheelchair, which is sent by at least one processor on the wheelchair. Structural parameters to the storage device.
  • the second determination module in order to implement the determination corresponding to the wheelchair structure parameter corresponding to the environmental data, is configured to determine a road condition corresponding to the current scene based on the environmental data; the road condition includes At least one of the following road conditions: straight roads, curves, and ramps; determining spatial parameters corresponding to the road conditions; and determining wheelchair structural parameters that pass through the road conditions based on the spatial parameters.
  • the second determination module is further configured to query a storage device to obtain a structural parameter corresponding to a current scene in which the wheelchair is located.
  • the storage device stores at least one set of scene-structure parameter data; the scene-structure parameter data includes environmental data of at least one scene and a corresponding wheelchair structure parameter.
  • the second determination module is further configured to input the environmental data into a structural parameter determination model, wherein the structural parameter
  • the determination model is a machine learning model, which is obtained after training based on environmental data of multiple scenarios and corresponding pairs of structural parameter samples of the wheelchair; the model is determined based on the structural parameters to determine the structural parameters of the wheelchair.
  • a computer-readable storage medium characterized in that the storage medium stores computer instructions, and when the computer reads the computer instructions in the storage medium, the computer runs the method for adaptively adjusting a wheelchair structural parameter according to any one of the above.
  • FIG. 1 is a schematic diagram of an exemplary smart wheelchair system according to some embodiments of the present invention.
  • FIG. 2 is a schematic diagram of exemplary hardware components and / or software components of an exemplary computing device according to some embodiments of the present invention
  • FIG. 3 is a schematic diagram of exemplary hardware components and / or software components of an exemplary mobile device according to some embodiments of the present invention.
  • FIG. 4 is a block diagram of an exemplary processing device according to some embodiments of the present invention.
  • FIG. 5 is an exemplary flowchart of adaptively adjusting a structural parameter of a wheelchair according to some embodiments of the present invention.
  • FIG. 6 is an exemplary flowchart of determining a target structure parameter of a wheelchair according to some embodiments of the present invention.
  • FIG. 7 is another exemplary flowchart for determining a wheelchair target structural parameter according to some embodiments of the present invention.
  • FIG. 8 is a block diagram of another exemplary processing device according to some embodiments of the present invention.
  • FIG. 9 is another exemplary flowchart of determining a wheelchair target structure parameter according to some embodiments of the present invention.
  • a flowchart is used in the present application to explain the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the various steps can be processed in reverse order or simultaneously. At the same time, you can add other operations to these processes, or remove a step or steps from these processes.
  • the wheelchair system or method can also be applied to any type of smart device or car other than a wheelchair.
  • the wheelchair system or method can be applied to different smart device systems, which include one or any combination of balance wheels, unmanned ground vehicles, wheelchairs, and the like.
  • Wheelchair systems can also be applied to any intelligent system that includes application management and / or distribution, such as systems for sending and / or receiving courier, and carrying people or goods to certain locations.
  • " wheelchair " and " smart wheelchair &quot are used interchangeably herein to refer to a device and equipment or tool that can be moved and operated automatically.
  • the invention relates to a system and method for adaptively adjusting the structural parameters of a wheelchair.
  • the environmental data around the wheelchair and the movement data of the wheelchair can be used to determine the target structural parameters of the wheelchair passing scene.
  • FIG. 1 is a schematic diagram of a smart wheelchair system 100 according to some embodiments of the present invention.
  • the smart wheelchair system 100 may be a platform that provides services for wheelchair automatic driving.
  • the smart wheelchair system 100 may include one or more wheelchairs 110, one or more terminals 120, a server 130, a network 140, and a storage device 150.
  • the server 130 may include a processing engine 112.
  • the wheelchair 110 can be moved, and the change of its mechanical structure is controlled according to different environments to adapt to different scenarios. For example, when turning, the wheelbase of the wheelchair 110 may be shortened to increase the stability of the wheelchair 110 when turning. For another example, when passing through steps or ramps, the wheelbase of the wheelchair 110 can be increased, the chassis height can be increased, and the seat inclination can be tilted forward or backward according to the situation of up and down slopes to ensure the safety and stability of the wheelchair 110 Sex.
  • the wheelchair 110 may be an electric wheelchair, a fuel cell wheelchair, a hybrid wheelchair, or a wheelchair equipped with a conventional internal combustion engine. In some embodiments, the wheelchair 110 includes a pair of front wheels and a pair of rear wheels.
  • the wheelchair 110 may include fewer / more wheels or equivalent structures, enabling the wheelchair 110 to move around.
  • the wheelchair 110 may be controlled, remotely controlled, and / or automatically controlled by a user (eg, a person taking the wheelchair 110 or a guardian thereof, or a person pushing the wheelchair, or another person assisting the use of the wheelchair).
  • the wheelchair 110 may be equipped with sensors 160-1, 160-2, 160-3 and the like mounted on the main body of the wheelchair 110.
  • the sensor 160 may be used to capture environmental data around the wheelchair 110 and / or movement data of the wheelchair 110 itself.
  • the sensor 160 may include, but is not limited to, lidar, radio radar, infrared sensor, GPS locator, ultrasonic sensor, IMU inertial measurement sensor, digital camera, photoelectric sensor, speed sensor, acceleration sensor, gyroscope, attitude sensor, etc. or any combination thereof .
  • the data captured by the sensors 160 may be transmitted to one or more components in the smart wheelchair system 100. For example, the sensor 160 may send the captured data to the server 130 for processing, or the sensor 160 may send the captured data to a processor located on the wheelchair 110.
  • the terminal 120 may include one or more devices with a data acquisition function, for example, a smart mobile device 120-1, a tablet computer 120-2, a notebook computer 120-3, etc., and determine the position of the wheelchair 110 through its built-in GPS positioning device And / or acquire environmental data around the wheelchair 110 through a photographing and / or camera function.
  • the smart mobile device 120-1 may include, but is not limited to, a smart phone, a Personal Digital Assistant (PDA), a handheld game console, smart glasses, a smart watch, a wearable device, a virtual display device, a display Enhancement equipment, etc. or any combination thereof.
  • the terminal 120 may send the obtained data to one or more components in the smart wheelchair system 100.
  • the terminal 120 may send the obtained data to the server 130 for processing.
  • the server 130 may be a single server or a server group.
  • the server farm may be centralized or distributed (for example, the server 130 may be a distributed system).
  • the server 130 may be local or remote.
  • the server 130 may be integrated inside the wheelchair 110 or may be remotely located.
  • the server 130 may access information and / or data stored in the storage device 150 and / or the terminal 120 through the network 140.
  • the server 130 may also directly access the internal storage unit and / or the storage unit built in the wheelchair 110 to obtain information and / or data.
  • the server 130 may be implemented on a cloud platform.
  • the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, between clouds, multiple clouds, or the like, or any combination of the above examples.
  • the server 130 may be implemented on the computing device shown in FIG. 2 or FIG. 3 of the present application.
  • the server 130 may be implemented on a computing device 200 as shown in FIG. 2, including one or more components in the computing device 200.
  • the server 130 may be implemented on a mobile device 300 as shown in FIG. 3, including one or more components in the computing device 300.
  • the server 130 may include a processing engine 132.
  • the processing engine 132 may process information and / or data related to the wheelchair 110 itself and its environment to perform one or more functions described herein. For example, the processing engine 132 may determine its own mechanical structure based on the motion information of the wheelchair 110 and the surrounding environment information.
  • the processing engine 132 may include one or more processors (eg, a single-core processor or a multi-core processor).
  • the processing engine 132 may include one or more hardware processors, such as a central processing unit (CPU), an application specific integrated circuit (ASIC), an application specific instruction set processor (ASIP), an image processor (GPU), a physical Computing Processor (PPU), Digital Signal Processor (DSP), Field Editable Gate Array (FPGA), Editable Logic Device (PLD), Controller, Microcontroller Unit, Reduced Instruction Set Computer (RISC), Microprocessor Or any combination of the above examples.
  • CPU central processing unit
  • ASIC application specific integrated circuit
  • ASIP application specific instruction set processor
  • GPU graphics processing
  • PPU physical Computing Processor
  • DSP Digital Signal Processor
  • FPGA Field Editable Gate Array
  • PLD Editable Logic Device
  • Controller Microcontroller Unit
  • RISC Reduced Instruction Set Computer
  • the network 140 may facilitate the exchange of information and / or data.
  • one or more components e.g., wheelchair 110, terminal 120, server 130, storage device 150, etc.
  • the server 130 may obtain data from the storage device 150 through the network 140.
  • the network 140 may be any one of a wired network or a wireless network, or a combination thereof.
  • the network 140 may include a cable network, a wired network, a fiber optic network, a telecommunications network, an intranet, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone Network (PSTN), Bluetooth network, ZigBee network, near field communication (NFC) network, etc. or any combination of the above examples.
  • the network 140 may include one or more network access points.
  • the storage device 150 may store data and / or instructions.
  • the storage device 130 may store data obtained from the wheelchair 110, the terminal 120, and the server 130.
  • the storage device 150 may store data and / or instructions for execution or use by the server 130, and the server 130 may implement or implement the exemplary methods described herein by executing or using the data and / or instructions.
  • the storage device 150 may include a large-capacity memory, a removable memory, a volatile read-write memory, a read-only memory (ROM), or the like, or any combination of the above examples.
  • Exemplary mass storage may include magnetic disks, optical disks, solid-state drives, and the like.
  • Exemplary removable memories may include flash disks, floppy disks, optical disks, memory cards, compact hard disks, magnetic tapes, and the like.
  • An exemplary volatile read-only memory may include a random access memory (RAM).
  • Exemplary random access memories may include dynamic random access memory (DRAM), dual data rate synchronous dynamic random access memory (DDRSDRAM), static random access memory (SRAM), thyristor random access memory (T-RAM), and zero-capacity memory (Z-RAM) )Wait.
  • DRAM dynamic random access memory
  • DDRSDRAM dual data rate synchronous dynamic random access memory
  • SRAM static random access memory
  • T-RAM thyristor random access memory
  • Z-RAM zero-capacity memory
  • Exemplary read-only memories may include masked read-only memory (MROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM) , Compact hard disk read-only memory (CD-ROM) and digital multi-function hard disk read-only memory.
  • the storage device 150 may be implemented on a cloud platform.
  • the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, between clouds, multiple clouds, or the like, or any combination of the above examples.
  • the storage device 150 may be connected to the network 140 to enable communication with one or more components in the smart wheelchair system 100 (eg, wheelchair 110, terminal 120, server 130, etc.). One or more components of the smart wheelchair system 100 may access data or instructions stored in the storage device 150 through the network 140. In some embodiments, the storage device 150 may directly connect or communicate with one or more components of the smart wheelchair system 100 (eg, wheelchair 110, server 130, etc.). In some embodiments, the storage device 150 may be part of the server 130.
  • FIG. 2 is a schematic diagram of an exemplary computing device 200 according to some embodiments of the present invention.
  • the terminal 120, the server 130, and / or the storage device 150 may be implemented on the computing device 200.
  • the processing engine 112 may be implemented on the computing device 200 and configured to implement the functions disclosed in this application.
  • the computing device 200 may include a processor 210, a memory 220, an input / output (I / O) 230, and a communication port 240.
  • the processor 210 may execute computer instructions (eg, program code) and may perform the functions of the server 140 according to the techniques described in the application.
  • the computer instructions may be used to perform specific functions described in this application, and the computer instructions may include, for example, programs, objects, components, data structures, programs, modules, and functions.
  • the processor 210 may process wheelchair surroundings data and / or motion data obtained from any component of the smart wheelchair system 100.
  • the processor 210 may include one or more hardware processors, such as a microcontroller, a microprocessor, a reduced instruction set computer (RISC), an application-specific integrated circuit (application specific integrated circuit) circuit (ASIC)), application-specific instruction-set processor (ASIP), central processing unit (CPU), graphics processing unit (GPU)) , Physical processing unit (physics processing unit (PPU)), digital signal processor (digital signal processor (DSP)), field programmable gate array (field programmable gate array (FPGA)), advanced RISC machine (advanced RISC machine ( ARM)), programmable logic device (PLD), any circuit or processor capable of performing one or more functions, or a combination of one or more of them.
  • RISC reduced instruction set computer
  • ASIC application specific integrated circuit
  • ASIP application-specific instruction-set processor
  • CPU central processing unit
  • GPU graphics processing unit
  • PPU Physical processing unit
  • DSP digital signal processor
  • FPGA field programmable gate array
  • FPGA field programmable gate array
  • the computing device 200 may also include multiple processors.
  • the operations and / or methods performed by one processor described in this application may also be performed jointly or separately by multiple processors.
  • the processor of the computing device 200 described in this application performs operations A and B
  • operations A and B may also be performed by two or more different processors in 200 in the computing device. Performed jointly or separately (for example, the first processor performs operation A and the second processor performs operation B, or the first processor and the second processor perform operations A and B together).
  • the memory 220 may store data / information obtained from the wheelchair 110, the terminal 120, the server 130, the storage device 150, and / or any other component of the smart wheelchair system 100.
  • the memory 220 may include one or a combination of mass storage, removable memory, volatile read-write memory, read-only memory (ROM), and the like.
  • Mass storage can include magnetic disks, optical disks, solid state drives, removable storage, and the like.
  • Removable memory may include flash drives, floppy disks, optical disks, memory cards, ZIP disks, magnetic tapes, and the like.
  • Volatile read-write memory may include random access memory (RAM).
  • RAM can include dynamic random access memory (DRAM), dual data rate synchronous dynamic random access memory (DDR, SDRAM), static random access memory (SRAM), thyristor random access memory (t-ram), zero-capacity random storage Access memory (Z-RAM), etc.
  • ROM can include mask read-only memory (MROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), optical disk read-only Memory (CD-ROM), compact disc for digital versatile discs, etc.
  • the memory 220 may store one or more programs and / or instructions for performing the exemplary methods described in this application.
  • the memory 220 may store a program, which may be used by the server 1/30 to determine the mechanical structure parameters of the wheelchair.
  • the input / output 230 may input and / or output signals, data, information, and the like. In some embodiments, the input / output 230 may enable data communication between the wheelchair 110 and the server 130. In some embodiments, the input / output 230 may include an input device and an output device.
  • the input device may include one or a combination of a keyboard, a mouse, a touch screen, and a microphone.
  • the output device may include one or a combination of a display device, a speaker, a printer, a projector, and the like.
  • the display device may include one or a combination of a liquid crystal display (LCD), a light emitting diode (LED) display, a flat panel display, a curved screen, a television device, a cathode ray tube (CRT), and a touch screen.
  • LCD liquid crystal display
  • LED light emitting diode
  • flat panel display a flat panel display
  • curved screen a television device
  • cathode ray tube CRT
  • touch screen a touch screen.
  • the communication port 240 may be connected to a network (eg, the network 140) to facilitate data communication.
  • the communication port 240 may establish a connection between the processing device 140 and the wheelchair 110, the terminal 120, and / or the storage device 150.
  • the connection may be one or a combination of wired connection, wireless connection, any connection capable of data transmission and / or reception, and the like.
  • the wired connection may include, for example, one or a combination of cables, optical cables, and telephone lines.
  • the wireless connection may include, for example, one or more of a Bluetooth TM link, a Wi-Fi TM link, a WiMAX TM link, a wireless local area network link, a ZigBee TM link, a mobile network link (eg, 3G, 4G, 5G, etc.) Combination.
  • the communication port 240 may be and / or include a standardized communication port, such as RS232, RS485, and the like.
  • FIG. 3 is a schematic diagram of exemplary hardware and / or software of an exemplary mobile device 300 according to some embodiments of the present invention.
  • the terminal 120 may be implemented on the mobile device 300.
  • the mobile device 300 may include a communication unit 310, a display unit 320, a graphics processor 330, a processor 340, an input / output unit 350, a memory 360, and a storage unit 390.
  • the mobile device 300 may further include a bus or a controller.
  • the mobile operating system 370 and one or more application programs 380 may be loaded from the storage unit 390 into the memory 360 and executed by the processor 340.
  • a GPS positioning program and / or a program related to data acquisition may be loaded into the memory 360 and executed by the processor 340.
  • the application program 380 may receive and display information about wheelchair mechanical structure parameter determination or other information related to the processing engine 132.
  • the input / output unit 350 can implement interaction with the smart wheelchair system 100 and provide the interaction-related information to other components in the smart wheelchair system 100 through the network 140, such as the server 130.
  • a computer hardware platform may be used as a hardware platform for one or more of the elements mentioned herein.
  • a computer with user interface elements can be used to implement a personal computer (PC) or any other form of workstation or terminal. With proper programming, a computer can also act as a server.
  • FIG. 4 is a block diagram of an exemplary processing device 400 according to some embodiments of the present invention.
  • the processing device 400 may include a first acquisition module 410, a first determination module 420, and a control module 430.
  • the processing device 400 may be implemented in a server 130 (also referred to as a built-in server 130 at this time) built in the wheelchair 110.
  • the first obtaining module 410 may obtain data.
  • the first acquisition module 410 may acquire data from one or more of the smart wheelchair system 100, the terminal 120, the storage device 150, the sensor 160, or any device or component disclosed in this application capable of storing data.
  • the acquired data may include one or more combinations of image data, video data, user instructions, algorithms, models, and the like.
  • the first obtaining module 410 may obtain environmental data of a current scene where the wheelchair is located and / or movement data of the wheelchair.
  • the environmental data may be temperature data, humidity data, location data, geographic conditions, or traffic conditions in the current scene.
  • the environmental data may be data related to wheelchair movement in the current scene, including but not limited to terrain features of the current scene (e.g., mountain lakes, trees, ramps, turns, sidewalks) , Lanes, lane lines, dividers, intersections, road markings, construction lots, etc.), mathematical parameters of the terrain features (e.g., length, width, height, curvature, arc length, etc.), the current location of the wheelchair, Whether there are driving obstacles (for example, pedestrians, stones, pits, steps, etc.) within a predetermined distance (for example, within 5 meters), whether driving conditions need to be changed within a predetermined distance, and the distance between a wheelchair and a driving state change point Or any combination thereof.
  • terrain features of the current scene e.g., mountain lakes, trees, ramps, turns, sidewalks
  • mathematical parameters of the terrain features e.g., length, width, height, curvature, arc length
  • the motion data may include, but is not limited to, the driving state of the wheelchair at the current time (e.g., straight, turning, uphill, downhill, etc.), the speed of the wheelchair at the current time, the acceleration of the wheelchair at the current time, the angular velocity of the wheelchair at the current time, Position, mileage of a wheelchair, etc., or any combination thereof.
  • the first obtaining module 410 may obtain data from the memory 220 in the processing engine 112 built in the wheelchair, and may also access the storage device 150 through the network 140 to obtain the data.
  • the first obtaining module 410 may obtain pre-stored environmental data from a local and / or cloud.
  • the first obtaining module 410 may obtain a target structure parameter of the wheelchair through the current scene from the local and / or cloud.
  • the first obtaining module 410 may be transmitted to other modules (for example, the first determining module 420) of the processing engine 112 for subsequent operations, or transmitted to the storage through the network 140
  • the device 150 is used for storage.
  • the first determining module 420 may be configured to determine a target structure parameter corresponding to the current scene based on the environmental data and / or the motion data.
  • the target structure parameter may be an optimized mechanical parameter of the wheelchair itself, so that the wheelchair can pass the current scene smoothly and safely.
  • the structural parameters of the wheelchair include, but are not limited to, wheelbase, wheelbase, chassis height, seat tilt, etc. or any combination thereof.
  • the wheelbase refers to the distance between the two vertical lines passing through the center of two wheels adjacent to the same side of the wheelchair and perpendicular to the longitudinal section of the wheelchair. , Front axis, rear axis).
  • the first determination module 420 may first determine a driving state of the wheelchair through the current scene based on the environmental data and / or the motion data. For example, when the wheelchair passes the current scene, it only needs to go straight, needs to turn, needs to go uphill or downhill, or any combination of driving conditions. Then, the target structure parameter is determined based on the driving state of the wheelchair.
  • the control module 430 may be configured to control an actuator on the wheelchair to adjust a current structural parameter of the wheelchair to the target structural parameter.
  • the actuator includes at least one motor mounted on a wheelchair.
  • the motor may receive a control signal generated by the control module 430 based on the target structural parameter determined in operation 520, and adjust the current structural parameter of the wheelchair to the target structural parameter.
  • the motor may perform at least one of the following operations based on the control signal: adjusting the length of the wheelbase; adjusting the width of the wheelbase; adjusting the height of the chassis; adjusting the tilt of the seat.
  • system and its modules shown in FIG. 4 may be implemented in various ways.
  • the system and its modules may be implemented by hardware, software, or a combination of software and hardware.
  • the hardware part can be implemented with dedicated logic;
  • the software part can be stored in the memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated design hardware.
  • a suitable instruction execution system such as a microprocessor or dedicated design hardware.
  • processor control code such as on a carrier medium such as a magnetic disk, CD or DVD-ROM, such as a read-only memory (firmware Such code is provided on a programmable memory or a data carrier such as an optical or electronic signal carrier.
  • the system and its modules of the present application can be implemented not only by hardware circuits such as VLSI or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, and the like. It can also be implemented by software executed by various types of processors, for example, or by a combination of the above-mentioned hardware circuit and software (for example, firmware).
  • FIG. 5 is an exemplary flowchart of adaptively adjusting a structural parameter of a wheelchair according to some embodiments of the present invention.
  • the process 500 may be performed by processing logic, which may include hardware (e.g., circuits, dedicated logic, programmable logic, microcode, etc.), software (running on a processing device to perform hardware simulation Instructions), etc. or any combination thereof.
  • One or more operations in the process 500 for adaptively adjusting the structural parameters of the wheelchair shown in FIG. 5 may be implemented by the smart wheelchair control system 100 shown in FIG. 1.
  • the process 500 may be stored in the storage device 150 in the form of instructions and executed and / or executed by the processing engine 112 (for example, the processor 220 of the computing device 200 shown in FIG. 2, the mobile device shown in FIG. 3 300 CPU 340).
  • environmental data of a current scene where the wheelchair is located and / or movement data of the wheelchair may be obtained. Operation 510 may be performed by the first acquisition module 410.
  • the current scene may be a three-dimensional space where the wheelchair is located at the current moment.
  • the position of the wheelchair at the current moment is used as the coordinate origin on three coordinate axes (i.e. , X-axis, y-axis, and z-axis) can be specified as the current scene in which the wheelchair is located.
  • the distance may be a preset value or may be adjusted, for example, manually adjusted and / or automatically adjusted by the system.
  • the environmental data may be temperature data, humidity data, location data, geographic conditions, or traffic conditions in the current scene.
  • the environmental data may be the above data related to wheelchair movement, for example, including but not limited to the terrain features of the current scene (e.g., mountain lakes, trees, sidewalks, lanes, lane lines, isolation zones, intersections Intersections, road signs, construction sites, etc.), mathematical parameters of the terrain features (e.g., length, width, height, curvature, arc length, etc.), the current position of the wheelchair, within a predetermined distance (e.g., within 5 meters) ) Whether there are driving obstacles (for example, pedestrians, stones, pits, steps, etc.), whether the driving state needs to be changed within a predetermined distance, the distance between the wheelchair and the driving state change point, or any combination thereof.
  • the terrain features of the current scene e.g., mountain lakes, trees, sidewalks, lanes, lane lines, isolation zones, intersections Intersections, road signs, construction sites, etc.
  • the motion data may include, but is not limited to, the driving status of the wheelchair at the current time (e.g., straight, turning, uphill, downhill, etc.), the speed of the wheelchair at the current time, the acceleration of the wheelchair at the current time, and the current time The angular velocity of the wheelchair, the posture of the wheelchair at the current moment, the mileage the wheelchair has traveled, etc., or any combination thereof.
  • the driving status of the wheelchair at the current time e.g., straight, turning, uphill, downhill, etc.
  • speed of the wheelchair at the current time e.g., straight, turning, uphill, downhill, etc.
  • the acceleration of the wheelchair at the current time e.g., the acceleration of the wheelchair at the current time
  • the current time e.g., the angular velocity of the wheelchair, the posture of the wheelchair at the current moment, the mileage the wheelchair has traveled, etc., or any combination thereof.
  • the environmental data may be obtained from a memory 220 in a processing engine 112 built into the wheelchair.
  • a map in a range of motion of the wheelchair is stored in the memory 220 in advance, and a high-definition map is more preferable.
  • the range of motion may be one block, one municipal district, one city, one province, one country, one continent, and / or the whole world.
  • the definitions of the high-definition map and the high-definition map in the unmanned field are the same and / or similar, and are not repeated here.
  • the high-definition map may include geographic feature data of a wheelchair movement range, for example, terrain features and mathematical parameters thereof.
  • the first obtaining module 410 may read the high-definition map in the storage unit 220 to obtain the geographical feature data of the wheelchair movement range as preset environment data. Contents included in the preset environment data may be the same and / or similar to the environment data.
  • the high-definition map pre-stored in the storage unit 220 may be updated at certain time intervals, for example, one day.
  • the environmental data may be obtained by accessing a cloud server and querying a high-definition map of the current scene where the wheelchair is located.
  • the processing engine 140 built in the wheelchair uses the communication port 240 to access the storage device 150 through the network 140 to obtain preset environmental data stored in the storage device 150.
  • the high-definition map stored in the storage device 150 can also be updated at certain time intervals, for example, one hour to ensure real-timeness and accuracy.
  • the environmental data and / or motion data may be captured by one or more sensors located on a wheelchair.
  • the one or more sensors may not be limited to laser radar, radio radar, GPS locator, ultrasonic sensor, IMU inertial measurement sensor, digital camera, photoelectric sensor, speed sensor, acceleration sensor, etc., or any combination thereof.
  • GPS can be used to determine the current position of the wheelchair
  • digital cameras / camcorders can be used to determine whether there are obstacles around the wheelchair or whether driving conditions need to be changed
  • lidar, radar sensors, and ultrasonic sensors alone and / or Combined use to determine the distance between the wheelchair and obstacles, terrain, driving state change points and / or obstacles' speed of movement (if any)
  • use inertial sensors to obtain the posture information of the wheelchair
  • use speed sensors to obtain the current wheelchair Speed
  • photoelectric sensors to get the mileage of the wheelchair, etc.
  • the one or more sensors may be sensors mounted on a wheelchair, for example, sensors 160-1, 160-2, 160-3, etc., or sensors on a terminal used by a user of the wheelchair, for example, terminal 120 Built-in GPS locator, attitude sensor and more.
  • the obtained environmental data and / or motion data and / or motion data are real-time to ensure the safety, stability and comfort of the wheelchair during driving, for example, changing the structural parameters of the wheelchair to pass various road conditions .
  • a target structure parameter corresponding to the current scene may be determined based on the environment data and / or motion data. Operation 520 may be performed by the first determination module 420.
  • the target structural parameter may be an optimized mechanical parameter of the wheelchair itself, so that the wheelchair can pass the current scene smoothly and safely.
  • the structural parameters of the wheelchair include, but are not limited to, wheelbase, wheelbase, chassis height, seat tilt, etc. or any combination thereof.
  • the driving state of the wheelchair through the current scene may be determined based on environmental data and / or motion data. For example, when the wheelchair passes the current scene, it only needs to go straight, needs to turn, needs to go uphill or downhill, or any combination of driving conditions.
  • the target structure parameter is determined based on the driving state of the wheelchair. For example, when a wheelchair goes straight through the current scene at high speed, the wheelbase length can be adjusted appropriately while reducing the chassis height and increasing the wheelbase to improve the stability of the wheelchair and reduce the risk of rollover.
  • a detailed description of determining a target structure parameter corresponding to the current scene can be found elsewhere in this specification (for example, FIG. 6 to FIG. 8), and is not repeated here.
  • the actuator on the wheelchair can be controlled to adjust the current structural parameter of the wheelchair to the target structural parameter.
  • Operation 530 may be performed by a control module 430.
  • the actuator includes at least one motor mounted on a wheelchair.
  • the motor may be any commercially available motor, for example, a DC motor or an AC motor. The type of the motor does not limit the solution of the present invention.
  • the motor may receive a control signal generated by the control module 430 based on the target structural parameter determined in operation 520, and adjust the current structural parameter of the wheelchair to the target structural parameter.
  • the current structural parameter may be a structural parameter of the wheelchair at the current moment.
  • the motor performs at least one of the following operations to achieve the above purpose. 1) Adjust the length of the wheelbase.
  • the wheelchair when the wheelchair can go straight through the current scene, among the target structural parameters obtained, when the target wheelbase exceeds the current wheelbase, the wheelchair can be made more stable, and the motor can increase the length of the wheelbase to the target wheelbase.
  • the motor can shorten the length of the wheelbase to ensure that the wheelchair can turn smoothly.
  • Adjust the width of the track For example, the adjustment of the wheelbase can be combined with the adjustment of the wheelbase. When the wheelbase increases, the wheelbase can also increase accordingly. When the wheelbase is shortened, the wheelbase can be shortened accordingly.
  • a value which can be any value between 0.55 and 0.64, such as 0.6. 3
  • adjust the height of the chassis For example, when the wheelchair needs to pass through a pothole, the height of the chassis can be increased to improve the wheelchair's passability.
  • Adjust the seat tilt For example, when a wheelchair passes a ramp, the user of the wheelchair may lean forward or lean back due to the gradient, and the seat tilt may be adjusted to improve the comfort and safety of the user.
  • the environment data of the current scene and its corresponding target structure parameter may be uploaded to the storage device 150 via the network 140 for storage.
  • the stored environmental data of the scene and its corresponding target structural parameters can be used as a reference when other wheelchairs pass the same environmental conditions.
  • FIG. 6 is an exemplary flowchart of determining a wheelchair target structure parameter according to some embodiments of the present invention.
  • the process 600 may be performed by the first determination module 420.
  • the process 600 may be performed by processing logic, which may include hardware (e.g., circuits, dedicated logic, programmable logic, microcode, etc.), software (running on a processing device to perform hardware simulation) Instructions), etc. or any combination thereof.
  • One or more operations in the process 600 for adaptively adjusting the structural parameters of the wheelchair shown in FIG. 5 may be implemented by the intelligent wheelchair control system 100 shown in FIG. 1.
  • the process 600 may be stored in the storage device 150 in the form of instructions and executed and / or executed by the processing engine 112 (for example, the processor 220 of the computing device 200 shown in FIG. 2, the mobile device shown in FIG. 3 300 CPU 340).
  • a road condition corresponding to the current scene may be determined based on the environmental data.
  • the road conditions may include straight roads, curves, ramps, etc., or any combination thereof.
  • the environmental data may indicate the road sections that the wheelchair needs to pass through the current scene, and the driving state required by the wheelchair when passing each road section, and then determine the road conditions corresponding to the current scene.
  • a spatial parameter corresponding to the road condition may be determined.
  • the spatial parameter may be a physical property of the road condition.
  • the spatial parameters may include, but are not limited to, a straight road length, a curve radius, a curve arc length, a slope angle, a slope distance, a slope height, and the like, or any combination thereof.
  • the spatial parameters may be obtained by extracting from a high-definition map built in and / or in the cloud. The accuracy of HD maps is centimeter level.
  • the spatial parameters may also be obtained by calculating environmental data captured by the one or more sensors, for example, by determining depth information of objects obtained through stereo matching of pictures and / or videos taken by a binocular camera. .
  • an intermediate structure parameter passing the road condition may be calculated based on the spatial parameter.
  • the intermediate structural parameter may be a reference value of a structural parameter of a wheelchair passing the road condition. For example, for a curve, when a wheelchair turns with a wheelbase A, it can pass through the curve, but the stability of the wheelchair is not good, and the risk of overturning may occur if it is not handled properly.
  • the intermediate structure parameter is an unoptimized value and only has a reference meaning. For the convenience of description, the determination process of the intermediate structure parameters is illustrated by taking an example of a wheelchair passing through a curve.
  • some of its mechanical parameters are determined, for example, the turning angle range of the steering wheel, the length of the front suspension (the distance from the center point of the front wheel to the front end of the wheelchair), the vehicle width, and the center distance of the steering axis.
  • the steering axis refers to the axis of rotation of the steering wheel when steering.
  • R is the radius of the curve
  • L is the wheelbase
  • C is the length of the front overhang
  • K is the width of the entire vehicle
  • M is the center distance of the steering shaft
  • ⁇ max is the maximum steering angle of the outer wheels of the steering wheels.
  • the structural parameter range may be a value range of a structural parameter of a mechanical model of the wheelchair, and the mechanical model may be obtained by mechanically modeling the wheelchair after data statistics. Taking the curve as an example, a value range of the wheelbase that can be safely and stably passed through the curve is obtained after counting the various wheelbases of the wheelchair when passing through multiple curves. When a wheelchair passes a curve with a value outside this value range, an accident such as a rollover may occur or a more obvious bump may occur.
  • the modeling process of the mechanical model can be found in the prior art, and is not repeated here.
  • the process 600 After obtaining the intermediate structure parameter, it may be determined whether the intermediate structure parameter is located within a value interval formed by the structure parameter range. If the intermediate structure parameter exceeds the value range formed by the structure parameter range, the process 600 proceeds to 650, otherwise, the process 600 proceeds to 660.
  • an endpoint value closer to the intermediate structural parameter in the structural parameter range may be determined as the target structural parameter.
  • the intermediate structural parameter if the intermediate structural parameter is not within a value interval formed by the structural parameter range, it indicates that if the wheelchair passes the road condition with the intermediate structural parameter, the stability of the wheelchair during exercise And the safety is low, which is not conducive to wheelchairs passing through the road conditions.
  • the endpoint value of the structural parameter range that is closer to the intermediate structural parameter will be determined as the target structural parameter to ensure the safety and stability of the wheelchair when passing the road condition.
  • the intermediate structure parameter will be determined as the target structure parameter.
  • the intermediate structural parameter if the intermediate structural parameter is located within a value interval formed by the structural parameter range, it means that if the wheelchair passes the road condition with the intermediate structural parameter, it can pass safely and stably. In this case, the intermediate structure parameter will be directly determined as the target structure parameter. In a subsequent process (for example, in 530 of process 500), the current structure parameter of the wheelchair will be adjusted to the target structure parameter. .
  • FIG. 7 is an exemplary flowchart of determining a target structure parameter of a wheelchair according to some embodiments of the present invention.
  • the process 700 may be performed by the first determination module 420.
  • the process 700 may be performed by processing logic, which may include hardware (e.g., circuits, dedicated logic, programmable logic, microcode, etc.), software (running on a processing device to perform hardware simulation) Instructions), etc. or any combination thereof.
  • One or more operations in the process 700 for obtaining a smart wheelchair model shown in FIG. 7 may be implemented by the smart wheelchair system 100 shown in FIG. 1.
  • the process 700 may be stored in the storage device 150 in the form of instructions and executed and / or executed by the processing engine 112 (for example, the processor 220 of the computing device 200 shown in FIG. 2, the mobile device shown in FIG. 3 300 CPU 340).
  • a preset structural parameter corresponding to the environmental data may be acquired.
  • the preset structure parameter may be data stored in advance on a local or server.
  • the preset structural parameters may be stored in correspondence with environmental data such as the location and road conditions of the scene. Based on the current scene location or road conditions and other environmental data, the corresponding preset structural parameters can be obtained directly from the local or server.
  • the preset structure parameter may be a target structure parameter used when one or more wheelchairs pass through the current scene. For a particular scene, one or more wheelchairs may have passed with the structural parameters corresponding to the scene.
  • the structural parameter may be calculated based on the environmental data of the scene (for example, obtained based on the process 600).
  • the wheelchair passing the scene can upload and store the scene and its corresponding structural parameters, or it can be stored in the local memory.
  • the structural parameters corresponding to the scene can be obtained directly through the network 140 as preset structural parameters, or by query
  • the local storage obtains a structural parameter that passes the scene as a preset structural parameter.
  • the preset structure parameter may be determined as the target structure parameter.
  • the first determining module 420 may directly determine the preset structural parameter as the target structural parameter, and the control module 430 may generate a control signal based on the target structural parameter to control the motor to the wheelchair The structural parameters are adjusted.
  • FIG. 8 is a block diagram of an exemplary processing device 800 according to some embodiments of the present invention.
  • the processing device 800 may include a second acquisition module 810, a second determination module 820, and a transmission module 830.
  • the processing device 800 may be implemented in a server 130 (eg, a cloud server) located outside the wheelchair 110.
  • the second acquisition module 810 may acquire environmental data of a current scene where the wheelchair is located.
  • the environmental data of the current scene where the wheelchair is located may be obtained by querying a high-definition map pre-stored in the internal memory of the wheelchair (eg, the storage unit 220) and / or stored in the storage device 150, or by a Captured by one or more sensors.
  • the second determination module 820 may determine a wheelchair structure parameter corresponding to the environmental data.
  • the wheelchair structural parameter may be a target structural parameter of a scene in which the wheelchair passes.
  • the second determination module 820 may calculate the wheelchair structure parameter based on the obtained environmental data.
  • the second determination module 820 may determine a road condition corresponding to the current scene of the wheelchair based on the environmental data, and obtain a spatial parameter corresponding to the road condition, and then use the spatial parameter to calculate an intermediate structural parameter that passes the road condition. After the intermediate structure parameter is determined, the second determining module 820 may compare the intermediate structure parameter with the range of the structure parameter.
  • the intermediate structural parameter is located within a value interval formed by the structural parameter range, the intermediate structural parameter is determined as a target structural parameter corresponding to a current scene where the wheelchair is located. Otherwise, the endpoint value closer to the intermediate structural parameter in the structural parameter range is determined as the target structural parameter corresponding to the current scene where the wheelchair is located.
  • the second determination module 820 may query a storage device (for example, the storage device 150) to obtain a structural parameter corresponding to the current scene in which the wheelchair is located.
  • the storage device stores at least one set of scene-structure parameter data, and the scene-structure parameter data includes at least one scene and a corresponding wheelchair structure parameter.
  • the scene and the corresponding wheelchair structural parameters may be uploaded to the storage device 150 for storage by the wheelchair passing through the scene.
  • the second determination module 820 may input the environmental data into a structural parameter determination model.
  • the structural parameter determination model may be one or more combinations of existing machine learning models, including but not limited to decision trees, random forests, logistic regression, support vector machines, naive Bayes, K nearest neighbor algorithms , K-means algorithm, Adaboost, neural network, Markov model, etc. or any combination thereof.
  • the structural parameter determination model may be obtained by training based on multiple scenes and their corresponding pairs of wheelchair structural parameter samples. The scene and the corresponding pair of wheelchair structural parameter sample pairs may include a scene and a target structural parameter when the wheelchair passes through the scene. After the environment of the scene is input, the second determining module 820 may directly determine a model based on the structural parameters to determine the structural parameters of the wheelchair.
  • the transmission module 830 may send the wheelchair structure parameter to at least one processor of the wheelchair.
  • the transmission module 830 may be sent to at least one processor of the wheelchair through the network 140, for example, the processor 210 of the processing engine 140 built in the wheelchair.
  • system and its modules shown in FIG. 8 may be implemented in various ways.
  • the system and its modules may be implemented by hardware, software, or a combination of software and hardware.
  • the hardware part can be implemented with dedicated logic; the software part can be stored in the memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated design hardware.
  • a suitable instruction execution system such as a microprocessor or dedicated design hardware.
  • processor control code such as on a carrier medium such as a magnetic disk, CD or DVD-ROM, such as a read-only memory (firmware Such code is provided on a programmable memory or a data carrier such as an optical or electronic signal carrier.
  • the system and its modules of the present application can be implemented not only by hardware circuits such as VLSI or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, and the like. It can also be implemented by software executed by various types of processors, for example, or by a combination of the above-mentioned hardware circuit and software (for example, firmware).
  • FIG. 9 is an exemplary flowchart of determining a target structure parameter of a wheelchair according to some embodiments of the present invention.
  • the process 900 may be performed by processing logic, which may include hardware (e.g., circuits, dedicated logic, programmable logic, microcode, etc.), software (running on a processing device to perform hardware simulation Instructions), etc. or any combination thereof.
  • One or more operations in the process 900 for acquiring the interference object set of the target to be measured shown in FIG. 8 may be implemented by the smart wheelchair system 100 shown in FIG. 1.
  • the process 800 may be stored in the storage device 150 in the form of instructions and executed and / or executed by the processing engine 112 (for example, the processor 220 of the computing device 200 shown in FIG. 2, the mobile device shown in FIG. 3 300 CPU 340).
  • the environmental data of the current scene where the wheelchair is located can be obtained. Operation 910 may be performed by the second acquisition module 810.
  • the environmental data of the current scene in the wheelchair may be uploaded after being acquired by the wheelchair, or the location of the scene where the wheelchair is only uploaded, and the second acquisition module queries the local storage and / or the storage device 150 according to the location information. HD map to get.
  • the content and acquisition method of the environmental data are similar to those described in the AND operation 510, and are not repeated here.
  • a wheelchair structure parameter corresponding to the environmental data may be determined. Operation 920 may be performed by the second determination module 820.
  • the wheelchair structure parameter may be a target structure parameter of a scene in which the wheelchair passes.
  • the road conditions corresponding to the current scene of the wheelchair may be determined based on the environmental data. The road conditions may include straight roads, curves, ramps, etc. or any combination thereof.
  • a spatial parameter corresponding to the road condition may be determined.
  • the spatial parameter may be a physical property of the road condition.
  • the spatial parameters may include, but are not limited to, a straight road length, a curve radius, a curve arc length, a slope angle, a slope distance, a slope height, and the like, or any combination thereof.
  • the spatial parameters may be obtained by extracting from built-in and / or high-definition maps in the cloud, or may be obtained by calculating environmental data captured by the one or more sensors. Then, based on the spatial parameters, the intermediate structural parameters that pass the road conditions may be calculated and compared with the structural parameter ranges. If the conditions are satisfied, for example, the intermediate structural parameters are formed by the structural parameter ranges. In the value range of, the intermediate structure parameter is determined as the target structure parameter corresponding to the current scene where the wheelchair is located.
  • the endpoint value closer to the intermediate structural parameter in the structural parameter range is determined as the target structural parameter corresponding to the current scene where the wheelchair is located.
  • the target structure parameter refers to other parts of the present disclosure, for example, the description in the part of FIG. 6.
  • the storage device may be queried to obtain the structural parameters corresponding to the current scene in which the wheelchair is located.
  • the storage device stores at least one set of scene-structure parameter data, and the scene-structure parameter data includes environmental data of at least one scene and a corresponding wheelchair structure parameter.
  • the structural parameters used when one or more wheelchairs pass may be counted and recorded, thereby forming at least one set of scene-structure parameter data.
  • the structural parameter may be calculated based on the environmental data of the scene (for example, obtained based on the process 600).
  • the wheelchair through the scene can upload and store the environmental data of the scene and its corresponding structural parameters, for example, stored in the storage device 150.
  • the data in the storage device 150 may be queried to obtain the structural parameters corresponding to the scene.
  • the environmental data may be input into a structural parameter determination model.
  • the structural parameter determination model may be one or more combinations of existing machine learning models, including but not limited to decision trees, random forests, logistic regression, support vector machines, naive Bayes, K nearest neighbor algorithms , K-means algorithm, Adaboost, neural network, Markov model, etc. or any combination thereof.
  • the structural parameter determination model may be obtained based on the environmental data of multiple scenarios and their corresponding pairs of wheelchair structural parameter samples.
  • the environmental data of the scene and its corresponding pair of wheelchair structural parameter samples may include the environmental data of a scene and the target structural parameters of the wheelchair as it passes through the scene.
  • the structural parameter determination model Before training, the structural parameter determination model has a plurality of initial model parameters, such as a learning rate, a hyperparameter, and the like.
  • the initial model parameters may be default values of the system, or may be adjusted and modified according to actual application conditions.
  • the training process of the initial model can be found in the prior art, and is not repeated here. When a certain preset condition is met, for example, the number of training samples reaches a predetermined number, the prediction accuracy of the model is greater than a predetermined accuracy threshold, or the value of the Loss Function is less than a predetermined value, the training process Will stop.
  • the structural parameter determination model can be used to determine the structural parameters of the wheelchair when passing through a scene.
  • the structure parameter determination model may be updated after a certain time interval, for example, one day, one week, and so on.
  • the newly generated scene-structure parameter pairs can be used to update the structure parameter determination model, for example, a scene-structure parameter pair uploaded by a wheelchair through a scene and / or a calculated scene-structure parameter Correct.
  • a model can be determined based on the structural parameters to determine the structural parameters of the wheelchair.
  • the structural parameter determination model may directly output a structural parameter corresponding to a wheelchair passing the scene.
  • the wheelchair structure parameter may be sent to at least one processor of the wheelchair. Operation 930 may be performed by the transmission module 830. In some embodiments, the wheelchair structure parameter may be sent to at least one processor of the wheelchair through the network 140, for example, the processor 210 of the processing engine 140 built into the wheelchair. The at least one processor may generate a control signal based on the received structural parameter of the wheelchair and send it to an execution device on the wheelchair, and the execution device adjusts the structural parameter of the wheelchair based on the control signal to pass the scene.
  • the structural parameters of the wheelchair can be automatically adjusted according to the scene in which the wheelchair is currently located, thereby improving the safety, stability and user comfort of the wheelchair during driving.
  • the possible beneficial effects may be any one or a combination of the foregoing, or any other beneficial effects that may be obtained.
  • the content disclosed in this application may have various variations and improvements.
  • the different system components described above are implemented by hardware devices, but may also be implemented only by software solutions. For example: Install the system on an existing server.
  • the location information disclosed herein may be provided through a firmware, a combination of firmware / software, a combination of firmware / hardware, or a combination of hardware / firmware / software.
  • All software or parts of it may sometimes communicate over a network, such as the Internet or other communication networks.
  • This type of communication can load software from one computer device or processor to another.
  • a hardware platform loaded from a management server or host computer of an intelligent wheelchair system into a computer environment, or other computer environment that implements the system, or a system with similar functions related to providing the information needed to determine the target structural parameters of the wheelchair. Therefore, another medium capable of transmitting software elements can also be used as a physical connection between local devices, such as light waves, radio waves, electromagnetic waves, etc., and is transmitted through cables, optical cables, or air.
  • the physical medium used for carrier waves, such as electrical cables, wireless connections, or optical cables, can also be considered as the medium that carries the software.
  • tangible "storage” media is restricted, other terms referring to computer or machine "readable media” refer to media that participates in the execution of any instruction by a processor.
  • the computer program code required for the operation of each part of this application can be written in any one or more programming languages, including object-oriented programming languages such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C ++, C #, VB.NET, Python Etc., conventional programming languages such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages.
  • the program code can be run entirely on the user's computer, or as a stand-alone software package on the user's computer, or partly on the user's computer, partly on a remote computer, or entirely on the remote computer or server.
  • the remote computer can be connected to the user's computer through any network form, for example, a local area network (LAN) or wide area network (WAN), or connected to an external computer (for example, through the Internet), or in a cloud computing environment, or as Use of services such as software as a service (SaaS).
  • LAN local area network
  • WAN wide area network
  • SaaS software as a service
  • numbers describing attributes and quantities are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about”, “approximately” or “substantially” in some examples. . Unless stated otherwise, “about”, “approximately” or “substantially” indicates that the number allows for a variation of ⁇ 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, and the approximate values may be changed according to the characteristics required by individual embodiments. In some embodiments, the numerical parameter should take the specified significant digits into account and adopt a general digits retention method. Although the numerical ranges and parameters used to confirm the breadth of the range in some embodiments of this application are approximate values, in specific embodiments, the setting of such values is as accurate as possible within the feasible range.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Traffic Control Systems (AREA)

Abstract

一种智能轮椅系统、方法及存储介质。方法由至少一个处理器实现，方法包括获取轮椅所处当前场景的环境数据和/或轮椅的运动数据(510)；基于环境数据和/或运动数据，确定对应于当前场景的目标结构参数(520)；进一步包括控制轮椅上的执行机构以调节轮椅的当前结构参数至目标结构参数(530)。智能轮椅系统的自适应调节方法，可以在获取轮椅当前所处场景后，基于场景数据动态调节轮椅的机械结构，达到更好的行驶稳定性和安全性。

Description

一种轮椅结构参数自适应调节方法、系统及存储介质 技术领域
本发明涉及智能轮椅技术领域，更具体的，涉及一种自适应调节轮椅结构参数的方法、系统及存储介质。
背景技术
随着社会发展带来的人口老龄化加剧，以及因事故造成的行动障碍人群数量的增加，对于轮椅的需求也在不断上升。伴随着智能驾驶技术的飞速发展，智能轮椅也开始出现，提供了智能化与人性化的服务。现有的智能轮椅，在行驶过程中可以根据周围的环境对轮椅的运动状态进行改变，例如，在通过坑洼路段时减速。但是，现有的智能轮椅不能实时的调节轮椅本身的机械结构参数，例如，加长轴距提高底盘高度以通过坑洼路段。这样的话可以提高轮椅的稳定性和安全性，同时带给轮椅使用者更好的舒适性。因此，需要一种根据轮椅周围环境对轮椅的机械结构参数进行调整的方法和/或系统以提供更佳的用户体验度。
发明内容
针对现有技术中的智能轮椅无法根据周围环境对自身机械结构参数进行调节的问题，本发明的一些实施例在于提供一种轮椅结构参数自适应调节方法、系统及存储介质，首先获取轮椅所处当前场景的环境数据和/或轮椅的运动数据，进一步基于环境数据和/或运动数据确定轮椅通过所述当前场景的目标结构参数，并对轮椅的当前结构参数进行调节，到达更好的稳定性、安全性和舒适性。
为了达到上述发明的目的，本发明提供的技术方案如下：
一种轮椅结构参数自适应调节方法，由至少一个处理器实现，所述方法可以包括以下一个或一个以上操作。可以获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据。可以基于所述环境数据和/或运动数据，确定对应于所述当前场景的目标结构参数。可以控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。
在一些实施例中，所述获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据可以包括以下至少一个操作。可以获取关于所述当前场景的预设环境数据，或者由位于在轮椅上的一个或一个以上的传感器所捕获的轮椅所处当前场景的环境数据和/或所述运动数据。
在一些实施例中，所述基于所述环境数据，确定对应于所述当前场景的目标结构参数可以包括以下至少一个操作。可以于所述环境数据，确定所述当前场景对应的路况；所述路况包括以下路况中的至少一个：直行道、弯道和坡道。可以确定对应于所述路况的空间参数。可以基于所述空间参数，确定通过所述路况的目标结构参数。
在一些实施例中，所述路况的空间参数，包括以下至少一个：直行道长度、弯道半径、弯道弧长、坡度角、坡面距离和坡道高度。
在一些实施例中，所述基于所述空间参数，确定通过所述路况的目标结构参数可以包括以下至少一个操作。可以基于所述空间参数，计算通过所述路况的中间结构参数。可以判断所述中间结构参数是否超出结构参数范围。响应于所述中间结构参数超出结构参数范围的判定，将所述结构参数范围中更接近于所述中间结构参数的端点值确定为所述目标结构参数。
在一些实施例中，所述基于所述空间参数，确定通过所述路况的目 标结构参数可以包括以下至少一个操作。可以基于所述空间参数，计算通过所述路况的中间结构参数。可以判断所述中间结构参数是否超出结构参数范围。响应于所述中间结构参数不超过所述结构参数范围的判定，将所述中间结构参数确定为所述目标结构参数。
在一些实施例中，所述基于所述环境数据确定对应于所述当前场景的目标结构参数可以包括以下至少一个操作。可以获取对应于所述环境数据的预设结构参数。可以将所述预设结构参数确定为所述目标结构参数。
在一些实施例中，所述结构参数包括以下至少一个：轴距、轮距、底盘高度和座椅倾斜度。
在一些实施例中，所述执行结构包括至少一个电机，所述电机用于接收所述至少一个处理器的控制信号以执行以下至少一个操作。可以调节所述轴距的长度。可以调节所述轮距的宽度。可以调节所述底盘高度。可以调节所述座椅倾斜度。
在一些实施例中，所述方法进一步包括以下操作。可以上传所述当前场景的环境数据及其所对应的目标结构参数。
一种轮椅结构参数自适应调节系统，所述系统包括至少一个处理器和至少一个存储设备，所述存储设备用于存储指令，当所述至少一个处理器执行所述指令时，实现以下至少一个操作。可以获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据。可以基于所述环境数据和/或运动数据，确定对应于所述当前场景的目标结构参数。可以控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。
在一些实施例中，为实现所述获取轮椅所处当前场景的环境数据和/ 或所述轮椅的运动数据，所述处理器被用于执行以下至少一个操作。可以获取关于所述当前场景的预设环境数据，或者由位于在轮椅上的一个或一个以上的传感器所捕获的轮椅所处当前场景的环境数据和/或所述运动数据。
在一些实施例中，为实现所述基于所述环境数据，确定对应于所述当前场景的目标结构参数，所述处理器被用于执行以下至少一个操作。可以于所述环境数据，确定所述当前场景对应的路况；所述路况包括以下路况中的至少一个：直行道、弯道和坡道。可以确定对应于所述路况的空间参数。可以基于所述空间参数，确定通过所述路况的目标结构参数。
在一些实施例中，所述路况的空间参数，包括以下至少一个：直行道长度、弯道半径、弯道弧长、坡度角、坡面距离和坡道高度。
在一些实施例中，为实现所述基于所述空间参数，确定通过所述路况的目标结构参数，所述处理器被用于执行以下至少一个操作。可以基于所述空间参数，计算通过所述路况的中间结构参数。可以判断所述中间结构参数是否超出结构参数范围。响应于所述中间结构参数超出结构参数范围的判定，将所述结构参数范围中更接近于所述中间结构参数的端点值确定为所述目标结构参数。
在一些实施例中，为实现所述基于所述空间参数，确定通过所述路况的目标结构参数，所述处理器被用于执行以下至少一个操作。可以基于所述空间参数，计算通过所述路况的中间结构参数。可以判断所述中间结构参数是否超出结构参数范围。响应于所述中间结构参数不超过所述结构参数范围的判定，将所述中间结构参数确定为所述目标结构参数。
在一些实施例中，为实现所述基于所述环境数据确定对应于所述当前场景的目标结构参数，所述处理器被用于执行以下至少一个操作。可以获取对应于所述环境数据的预设结构参数。可以将所述预设结构参数确定为所述目标结构参数。
在一些实施例中，所述结构参数包括以下至少一个：轴距、轮距、底盘高度和座椅倾斜度。
在一些实施例中，所述执行结构包括至少一个电机，所述电机用于接收所述至少一个处理器的控制信号以执行以下至少一个操作。可以调节所述轴距的长度。可以调节所述轮距的宽度。可以调节所述底盘高度。可以调节所述座椅倾斜度。
在一些实施例中，所述处理器被进一步用于执行以下操作。可以上传所述当前场景的环境数据及其所对应的目标结构参数。
一种轮椅结构参数自适应调节系统，所述系统包括第一获取模块、第一确定模块和控制模块。所述第一获取模块，用于获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据。所述第一确定模块，用于基于所述环境数据和/或运动数据，确定对应于所述当前场景的目标结构参数。所述控制模块，用于控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。
在一些实施例中，所述第一获取模块用于获取关于所述当前场景的预设环境数据，或者通过位于在轮椅上的一个或一个以上的传感器所捕获的轮椅所处当前场景的环境数据和/或所述运动数据。
在一些实施例中，所述第一确定模块用于基于所述环境数据，确定 所述当前场景对应的路况；所述路况包括以下路况中的至少一个：直行道、弯道和坡道。所述第一确定模块还用于确定对应于所述路况的空间参数。所述第一确定模块还用于基于所述空间参数，确定通过所述路况的目标结构参数。
在一些实施例中，所述路况的空间参数，包括以下至少一个：直行道长度、弯道半径、弯道弧长、坡度角、坡面距离和坡道高度。
在一些实施例中，为实现所述基于所述空间参数，确定通过所述路况的目标结构参数，所述第一确定模块还用于基于所述空间参数，计算通过所述路况的中间结构参数；判断所述中间结构参数是否超出结构参数范围；响应于所述中间结构参数超出结构参数范围的判定，将所述结构参数范围中更接近于所述中间结构参数的端点值确定为所述目标结构参数。
在一些实施例中，为实现所述基于所述空间参数，确定通过所述路况的目标结构参数，所述第一确定模块还用于基于所述空间参数，计算通过所述路况的中间结构参数；判断所述中间结构参数是否超出结构参数范围；响应于所述中间结构参数不超过所述结构参数范围的判定，将所述中间结构参数确定为所述目标结构参数。
在一些实施例中，为实现所述基于所述环境数据确定对应于所述当前场景的目标结构参数，所述第一确定模块还用于获取对应于所述环境数据的预设结构参数，可以将所述预设结构参数确定为所述目标结构参数。
在一些实施例中，所述结构参数包括以下至少一个：轴距、轮距、底盘高度和座椅倾斜度。
在一些实施例中，所述执行结构包括至少一个电机，所述电机用于 接收所述控制模块的控制信号以执行以下至少一个操作。可以调节所述轴距的长度。可以调节所述轮距的宽度。可以调节所述底盘高度。可以调节所述座椅倾斜度。
在一些实施例中，所述系统还包括通信模块，被用于上传所述当前场景的环境数据及其所对应的目标结构参数。
一种计算机可读存储介质，其特征在于，所述存储介质存储计算机指令，当计算机读取存储介质中的计算机指令后，计算机运行如上述任意一项所述轮椅结构参数自适应调节方法。
一种用于轮椅结构参数自适应调节的方法，所述方法有至少一个处理器实现。所述方法可以包括以下至少一个操作。可以获取所述轮椅当前所处场景的环境数据。可以确定对应与于所述环境数据的轮椅结构参数。可以发送所述轮椅结构参数至所述轮椅上的至少一个处理器。
在一些实施例中，所述方法可以进一步包括以下至少一个操作。可以接收并存储所述轮椅上的至少一个处理器发送的所述轮椅所处当前场景的环境数据及其对应的轮椅结构参数至所述存储设备。
在一些实施例中，所述确定对应与于所述环境数据的轮椅结构参数，可以包括以下至少一个操作。可以基于所述环境数据，确定所述当前场景对应的路况；所述路况包括以下路况中的至少一个：直行道、弯道和坡道。可以确定对应于所述路况的空间参数。可以基于所述空间参数，确定通过所述路况的轮椅结构参数。
在一些实施例中，所述确定对应与于所述环境数据的轮椅结构参数，可以包括以下至少一个操作。可以查询存储设备，获取与轮椅所处当前场 景的环境数据对应的结构参数，所述存储设备存储有至少一组场景-结构参数数据；所述场景-结构参数数据包括至少一个场景的环境数据及其所对应的轮椅结构参数。
在一些实施例中，所述确定对应与于所述环境数据的轮椅结构参数，可以包括以下至少一个操作。可以将所述环境数据输入至结构参数确定模型，其中，所述结构参数确定模型为机器学习模型，基于多个场景的环境数据及其对应的轮椅结构参数样本对进行训练后得到。可以基于所述结构参数确定模型，确定轮椅的结构参数。
一种用于轮椅结构参数自适应调节的系统，所述系统包括至少一个处理器和至少一个存储设备，所述存储设备用于存储指令，当所述至少一个处理器执行所述指令时，实现以下至少一个操作。可以获取所述轮椅当前所处场景的环境数据。可以确定对应与于所述环境数据的轮椅结构参数。可以发送所述轮椅结构参数至所述轮椅上的至少一个处理器。
在一些实施例中，所述处理器可进一步实现以下至少一个操作。可以接收并存储所述轮椅上的至少一个处理器发送的所述轮椅所处当前场景的环境数据及其对应的轮椅结构参数至所述存储设备。
在一些实施例中，为实现所述确定对应与于所述环境数据的轮椅结构参数，所述处理器可执行以下至少一个操作。可以基于所述环境数据，确定所述当前场景对应的路况；所述路况包括以下路况中的至少一个：直行道、弯道和坡道。可以确定对应于所述路况的空间参数。可以基于所述空间参数，确定通过所述路况的轮椅结构参数。
在一些实施例中，为实现所述确定对应与于所述环境数据的轮椅结 构参数，所述处理器可执行以下至少一个操作。可以查询存储设备，获取与轮椅所处当前场景的环境数据对应的结构参数，所述存储设备存储有至少一组场景-结构参数数据；所述场景-结构参数数据包括至少一个场景的环境数据及其所对应的轮椅结构参数。
在一些实施例中，为实现所述确定对应与于所述环境数据的轮椅结构参数，所述处理器可执行以下至少一个操作。可以将所述环境数据输入至结构参数确定模型，其中，所述结构参数确定模型为机器学习模型，基于多个场景及其对应的轮椅结构参数样本对进行训练后得到。可以基于所述结构参数确定模型，确定轮椅的结构参数。
一种用于轮椅结构参数自适应调节的系统，所述系统包括第二获取模块、第二确定模块和传输模块。所述第二获取模块用于获取所述轮椅当前所处场景的环境数据。所述第二确定模块用于确定对应与于所述环境数据的轮椅结构参数。所述传输模块用于发送所述轮椅结构参数至所述轮椅上的至少一个处理器。
在一些实施例中，所述系统可进一步包括接收模块，所述接收模块用于接收并存储所述轮椅上的至少一个处理器发送的所述轮椅所处当前场景的环境数据及其对应的轮椅结构参数至所述存储设备。
在一些实施例中，为实现所述确定对应与于所述环境数据的轮椅结构参数，所述第二确定模块用于基于所述环境数据，确定所述当前场景对应的路况；所述路况包括以下路况中的至少一个：直行道、弯道和坡道；确定对应于所述路况的空间参数；基于所述空间参数，确定通过所述路况的轮椅结构参数。
在一些实施例中，为实现所述确定对应与于所述环境数据的轮椅结构参数，所述第二确定模块还用于查询存储设备，获取与轮椅所处当前场景对应的结构参数，所述存储设备存储有至少一组场景-结构参数数据；所述场景-结构参数数据包括至少一个场景的环境数据及其所对应的轮椅结构参数。
在一些实施例中，为实现所述确定对应与于所述环境数据的轮椅结构参数，所述第二确定模块还用于将所述环境数据输入至结构参数确定模型，其中，所述结构参数确定模型为机器学习模型，基于多个场景的环境数据及其对应的轮椅结构参数样本对进行训练后得到；基于所述结构参数确定模型，确定轮椅的结构参数。
一种计算机可读存储介质，其特征在于，所述存储介质存储计算机指令，当计算机读取存储介质中的计算机指令后，计算机运行如上述任意一项所述轮椅结构参数自适应调节方法。
附加的特征将在下面的描述中部分地阐述，并且对于本领域技术人员来说，通过查阅以下内容和附图将变得显而易见，或者可以通过实例的产生或操作来了解。本发明的特征可以通过实践或使用以下详细实例中阐述的方法、工具和组合的各个方面来实现和获得。
附图说明
根据示例性实施例可以进一步描述本申请。参考附图可以详细描述所述示例性实施例。所述实施例并非限制性的示例性实施例，其中相同的附图标记代表附图的几个视图中相似的结构，并且其中：
图1是根据本发明的一些实施例所示的一个示例性智能轮椅系统的 示意图；
图2是根据本发明的一些实施例所示的一个示例性计算设备的示例性硬件组件和/或软件组件的示意图；
图3是根据本发明的一些实施例所示的一个示例性移动设备的示例性硬件组件和/或软件组件的示意图；
图4是根据本发明的一些实施例所示的一个示例性处理设备的框图；
图5是根据本发明的一些实施例所示的自适应调节轮椅结构参数的示例性流程图；
图6是根据本发明的一些实施例所示的确定轮椅目标结构参数的示例性流程图；
图7是根据本发明的一些实施例所示的另一种确定轮椅目标结构参数的示例性流程图；
图8是根据本发明的一些实施例所示的另一种示例性处理设备的框图；
图9是根据本发明的一些实施例所示的另一种确定轮椅目标结构参数的示例性流程图。
具体实施方式
为了更清楚地说明本申请的实施例的技术方案，下面将对实施例描述中所需要使用的附图作简单的介绍。显而易见地，下面描述中的附图仅仅是本申请的一些示例或实施例，对于本领域的普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图将本申请应用于其他类似情景。除非从语言环境中显而易见或另做说明，图中相同标号代表相同结 构或操作。
如本申请和权利要求书中所示，除非上下文明确提示例外情形，“一”、“一个”、“一种”和/或“该”等词并非特指单数，也可包括复数。一般说来，术语“包括”与“包含”仅提示包括已明确标识的步骤和元素，而这些步骤和元素不构成一个排它性的罗列，方法或者设备也可能包含其他的步骤或元素。
虽然本申请对根据本申请的实施例的系统中的某些模块做出了各种引用，然而，任何数量的不同模块可以被使用并运行在车辆客户端和/或服务器上。所述模块仅是说明性的，并且所述系统和方法的不同方面可以使用不同模块。
本申请中使用了流程图用来说明根据本申请的实施例的系统所执行的操作。应当理解的是，前面或下面操作不一定按照顺序来精确地执行。相反，可以按照倒序或同时处理各种步骤。同时，也可以将其他操作添加到这些过程中，或从这些过程移除某一步或数步操作。
此外，本申请仅描述了与轮椅相关的系统和方法，可以理解的是，本申请中的描述仅仅是一个实施例。该轮椅系统或方法也可以应用于除轮椅以外的其他任何类型的智能设备或汽车中。例如，轮椅系统或方法可以应用于不同的智能设备系统中，这些智能设备系统包括摆轮、无人地面车辆、轮椅等中的一种或任意几种的组合。轮椅系统还可以应用到包括应用管理和/或分发的任何智能系统，例如用于发送和/或接收快递，以及将人员或货物运载到某些位置的系统。
本申请的术语“轮椅”、“智能轮椅”可互换地使用，用于指代可移 动和自动操作的装置、设备或工具。
在一个方面，本发明涉及自适应调节轮椅结构参数的系统和方法。可以使用轮椅周围的环境数据和轮椅的运动数据来确定轮椅通过场景的目标结构参数。
{{图1}}
图1是根据本发明的一些实施例所示的一种智能轮椅系统100的示意图。例如，智能轮椅系统100可以是一个为轮椅自动驾驶提供服务的平台。智能轮椅系统100可以包括一个或一个以上轮椅110、一个或一个以上终端120、一个服务器130、一个网络140和一个存储设备150。服务器130可以包括一个处理引擎112。
在一些实施例中，轮椅110可以移动，并根据所处环境的不同控制自身机械结构的改变以适应不同的场景。例如，在转弯时，轮椅110的轴距可以缩短，以增加轮椅110在过弯时的稳定性。又例如，在通过台阶或坡道时，轮椅110的轴距可以增长、底盘高度可以增高、座椅倾斜度可根据上下坡的情况进行前倾或后仰，以保证轮椅110的安全性和稳定性。轮椅110可以是电动轮椅、燃料电池轮椅、混合动力轮椅或安装有传统内燃机的轮椅。在一些实施例中，轮椅110包括可以包括一对前轮和一对后轮。然而，可以预见的是，轮椅110可以包括更少/更多的车轮或等效结构，使轮椅110能够四处移动。在一些实施例中，轮椅110可以由使用者(例如，乘坐轮椅110的人或者其监护人或者推动轮椅的人或者其他辅助轮椅使用的人)进行操控、远程操控和/或自动操控。
如图1所示，轮椅110可以配备有安装在轮椅110主体上的传感器160-1、160-2、160-3等。在一些实施例中，传感器160可以用于捕获轮椅110周围的环境数据和/或轮椅110自身的运动数据。传感器160可以包括但不限于激光雷达、无线电雷达、红外传感器、GPS定位器、超声波传感器、IMU惯性测量传感器、数码相机、光电传感器、速度传感器、加速度传感器、陀螺仪、姿态传感器等或其任意组合。在一些实施例中，传感器160所捕获到的数据可以传输至智能轮椅系统100中的一个或一个以上部件中。例如，传感器160可以将捕获到的数据发送至服务器130中进行处理，又或者传感器160可以将捕获到的数据发送给位于轮椅110上的处理器。
终端120可以包括一个或一个以上带有数据获取功能的设备，例如，智能移动设备120-1、平板电脑120-2、笔记本电脑120-3等，通过自身内置的GPS定位装置确定轮椅110的位置和/或通过拍照和/或摄像功能获取轮椅110周围的环境数据。在一些实施例中，智能移动设备120-1可以包括但不限于智能手机、个人数码助理(Personal Digital Assistance，PDA)、掌上游戏机、智能眼镜、智能手表、可穿戴设备、虚拟显示设备、显示增强设备等或其任意组合。在一些实施例中，终端120可以将所获得的数据发送至智能轮椅系统100中的一个或一个以上部件中。例如，终端120可以将所获得的数据发送至服务器130进行处理。
在一些实施例中，服务器130可以是一个单个的服务器或者一个服务器群组。所述服务器群可以是集中式的或分布式的(例如，服务器130可以是一个分布式的系统)。在一些实施例中，服务器130可以是本地的或 远程的。例如，服务器130可以是集成在轮椅110内部，也可以是位于远程的。在一些实施例中，服务器130可以通过网络140访问存储在存储设备150和/或终端120中的信息和/或数据。服务器130也可以直接访问自身内部的存储单元和/或内置与轮椅110中的存储单元以获取信息和/或数据。在一些实施例中，服务器130可以在一个云平台上实现。仅仅举个例子，所述云平台可以包括私有云、公共云、混合云、社区云、分布云、云之间、多重云等或上述举例的任意组合。在一些实施例中，服务器130可以在与本申请图2或图3所示的计算设备上实现。例如，服务器130可以在如图2所示的一个计算设备200上实现，包括计算设备200中的一个或多个部件。再例如，服务器130可以在如图3所示的一个移动设备300上实现，包括计算设备300中的一个或多个部件。
在一些实施例中，服务器130可以包括一个处理引擎132。处理引擎132可以处理与轮椅110自身及其所处环境相关的信息和/或数据以执行本申请描述的一个或多个功能。例如，处理引擎132可以基于轮椅110的运动信息和周围环境信息确定自身机械结构。在一些实施例中，处理引擎132可以包括一个或多个处理器(例如，单核处理器或多核处理器)。仅仅举个例子，处理引擎132可以包括一个或多个硬件处理器，例如中央处理器(CPU)、专用集成电路(ASIC)、专用指令集处理器(ASIP)、图像处理器(GPU)、物理运算处理器(PPU)、数字信号处理器(DSP)、现场可编辑门阵列(FPGA)、可编辑逻辑器件(PLD)、控制器、微控制器单元、精简指令集计算机(RISC)、微处理器等或上述举例的任意组合。
网络140可以促进信息和/或数据的交换。在一些实施例中，智能轮 椅系统100中的一个或多个部件(例如，轮椅110、终端120、服务器130和存储设备150等)可以通过网络140向智能轮椅系统100中的其他部件发送信息和/或数据。例如，服务器130可以通过网络140从存储设备150处获取数据。在一些实施例中，网络140可以是有线网络或无线网络中的任意一种，或其组合。例如，网络140可以包括电缆网络、有线网络、光纤网络、远程通信网络、内联网、互联网、局域网(LAN)、广域网(WAN)、无线局域网(WLAN)、城域网(MAN)、公共开关电话网络(PSTN)、蓝牙网络、ZigBee网络、近场通讯(NFC)网络等或上述举例的任意组合。在一些实施例中，网络140可以包括一个或多个网络接入点。
存储设备150可以存储数据和/或指令。在一些实施例中，存储设备130可以存储从轮椅110、终端120和服务器130处获得的数据。在一些实施例中，存储设备150可以存储供服务器130执行或使用的数据和/或指令，服务器130可以通过执行或使用所述数据和/或指令以实现本申请描述的示例性方法。在一些实施例中，存储设备150可以包括大容量存储器、可移动存储器、挥发性读写存储器、只读存储器(ROM)等或上述举例的任意组合。示例性的大容量存储器可以包括磁盘、光盘、固态硬盘等。示例性的可移动存储器可以包括闪存盘、软盘、光盘、记忆卡、压缩硬盘、磁带等。示例性的挥发性只读存储器可以包括随机存储器(RAM)。示例性的随机存储器可以包括动态随机存储器(DRAM)、双数据率同步动态随机存储器(DDRSDRAM)、静态随机存储器(SRAM)、可控硅随机存储器(T-RAM)和零电容存储器(Z-RAM)等。示例性的只读存储器可以包括掩蔽型只读存储器(MROM)、可编程只读存储器(PROM)、可擦除可编程只读存储 器(EPROM)、电可擦除可编程只读存储器(EEPROM)、压缩硬盘只读存储器(CD-ROM)和数字多功能硬盘只读存储器等。在一些实施例中，存储设备150可以在一个云平台上实现。仅仅举个例子，所述云平台可以包括私有云、公共云、混合云、社区云、分布云、云之间、多重云等或上述举例的任意组合。
在一些实施例中，存储设备150可以与网络140连接以实现与智能轮椅系统100中的一个或多个部件(例如，轮椅110、终端120、服务器130等)之间的通信。智能轮椅系统100的一个或一个以上部件可以通过网络140访问存储在存储设备150中的数据或指令。在一些实施例中，存储设备150可以直接与智能轮椅系统100的一个或一个以上部件(例如，轮椅110、服务器130等)连接或通信。在一些实施例中，存储设备150可以是服务器130的一部分。
{{图2}}
图2是根据本发明的一些实施例所示的一种示例性计算设备200的示意图。终端120、服务器130和/或存储设备150可以在计算设备200上实现。例如，处理引擎112可以在计算设备200上实现并被配置为实现本申请中所披露的功能。如图2所示，计算装置200可包括处理器210、存储器220、输入/输出(I/O)230和通信端口240。
处理器210可以执行计算机指令(例如，程序代码)并可以根据申请中描述的技术执行服务器140的功能。所述计算机指令可以用于执行本申请中描述的特定功能，所述计算机指令可以包括例如程序、对象、组件、 数据结构、程序、模块和功能。例如，处理器210可以处理从智能轮椅系统100的任何组件获取的轮椅周围环境数据和/或运动数据。在一些实施例中，处理器210可以包括一个或多个硬件处理器，例如微控制器、微处理器、精简指令集计算机(reduced instruction set computer(RISC))、特定应用集成电路(application specific integrated circuit(ASIC))、应用程序特定的指令集处理器(application-specific instruction-set processor(ASIP))、中央处理单元(central processing unit(CPU))、图形处理单元(graphics processing unit(GPU))、物理处理单元(physics processing unit(PPU))、数字信号处理器(digital signal processor(DSP))、现场可编程门阵列(field programmable gate array(FPGA))、先进的RISC机器(advanced RISC machine(ARM))、可编程逻辑器件(programmable logic device(PLD))、能够执行一个或多个功能的任何电路或处理器等其中一种或几种的组合。
仅用于说明，在计算设备200中仅描述一个处理器。然而，需要说明的是，计算装置200也可以包括多个处理器。由本申请中描述一个处理器执行的操作和/或方法也可以由多个处理器共同或分别执行。例如，如果本申请中描述的计算设备200的处理器执行操作A和操作B，应当理解的是，操作A和操作B也可以由计算装置中的200中的两个或两个以上不同处理器共同或分别执行(例如，第一处理器执行操作A和第二处理器执行操作B，或第一处理器和第二处理器共同执行操作A和B)。
存储器220可以存储从轮椅110、终端120、服务器130、存储设备150和/或智能轮椅系统100的任何其它组件获取的数据/信息。在一些实施例中，存储器220可包括大容量存储器、可移除存储器、易失性读写存储 器、只读存储器(ROM)等其中一种或几种的组合。大容量存储可以包括磁盘、光盘、固态硬盘、移动存储等。可移除存储器可以包括闪存驱动器、软盘、光盘、存储卡、ZIP磁盘、磁带等。易失性读写存储器可以包括随机存取存储器(RAM)。RAM可以包括动态随机存储器(DRAM)、双数据率同步动态随机存取存储器(DDR SDRAM)、静态随机存取存储器(SRAM)、可控硅随机存取存储器(t-ram)、零电容随机存取存储器(Z-RAM)等。ROM可以包括掩模只读存储器(MROM)、可编程的只读存储器(PROM)、可擦除可编程只读存储器(EPROM)，电可擦除可编程只读存储器(EEPROM)、光盘只读存储器(CD-ROM)、数字多功能光盘的光盘等。在一些实施例中，存储器220可以存储一个或多个程序和/或指令，用于执行本申请中描述的示例性方法。例如，存储器220可以存储程序，所述程序可以用于服务器1/30确定轮椅的机械结构参数。
输入/输出230可以输入和/或输出信号、数据、信息等。在一些实施例中，输入/输出230可以实现轮椅110与服务器130之间的数据通信。在一些实施例中，输入/输出230可以包括输入设备和输出设备。输入设备可以包括键盘、鼠标、触摸屏、麦克风等其中一种或几种的组合。输出装置可以包括显示装置、扬声器、打印机、投影仪等其中一种或几种的组合。所述显示装置可以包括液晶显示器(LCD)、发光二极管(LED)显示器、平板显示器、弧形屏幕、电视装置、阴极射线管(CRT)、触摸屏等其中一种或几种的组合。
通信端口240可以连接网络(例如，网络140)，以便于数据通信。通信端口240可以在处理设备140和轮椅110、终端120和/或存储设备150 之间建立连接。所述连接可以是有线连接、无线连接、任何能够实现数据传输和/或接收的连接等其中一种或几种的组合。所述有线连接可以包括例如电缆、光缆、电话线等其中一种或几种的组合。所述无线连接可以包括，例如，蓝牙 TM链接、Wi-Fi TM链接、WiMAX TM链路、无线局域网链接、ZigBee TM链接、移动网络链接(例如，3G、4G、5G等)其中一种或几种的组合。在一些实施例中，通信端口240可以是和/或包括标准化通信端口，如RS232、RS485等。
{{图3}}
图3是根据本发明的一些实施例所示的一个示例性的移动设备300的示例性硬件和/或软件的示意图。终端120可以在移动设备300上实现。如图3所示，移动设备300可以包括一个通讯单元310、一个显示单元320、一个图形处理器330、一个处理器340、一个输入/输出单元350、一个内存360和一个存储单元390。移动设备300中还可以包括一个总线或者一个控制器。在一些实施例中，移动操作系统370和一个或多个应用程序380可以从存储单元390加载到内存360中，并由处理器340执行。例如，GPS定位程序和/或与数据获取相关的程序(例如，拍照、摄像等)可以被加载到内存360中有处理器340执行。在一些实施例中，应用程序380可以接收和显示与处理引擎132有关的轮椅机械结构参数确定或其他信息的信息。输入/输出单元350可以实现与智能轮椅系统100的交互，并将交互相关信息通过网络140提供给智能轮椅系统100中的其他部件，如服务器130。
为了实现本申请中描述的各种模块、单元及其功能，计算机硬件平 台可以用作这里提到的一个或多个元件的硬件平台。一个拥有用户界面元件的计算机可以用于实现个人计算机(PC)或者其它任何形式的工作站或终端设备。通过合适的编程，一个计算机也可以充当一台服务器。
{{图4}}
图4是根据本发明的一些实施例所示的示例性处理设备400的框图。如图所示，处理设备400可以包括第一获取模块410、第一确定模块420和控制模块430。处理设备400可以实现在内置于轮椅110中的服务器130中(此时也可以被称为内置服务器130)。
第一获取模块410可以获取数据。在一些实施例中，第一获取模块410可以从智能轮椅系统100、终端120、存储设备150、传感器160或本申请中公开的能够存储数据的任何设备或组件中的一个或一个以上获取数据。所获取的数据可以包括图像数据、视频数据、用户指令、算法、模型等中的一种或多种组合。在一些实施例中，第一获取模块410可以获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据。所述环境数据可以是在所述当前场景中的温度数据、湿度数据、位置数据、地理情况或交通状况等。在一些实施例中，所述环境数据可以是在所述当前场景中的与轮椅运动相关的数据，包括但不限于当前场景的地形特征(例如，高山湖泊、树木、坡道、转弯处、人行道、车道、车道线、隔离带、交叉路口、道路标识、施工地段等)、所述地形特征的数学参数(例如，长、宽、高、曲率、弧长等)、轮椅当前所处位置、、预定距离内(例如，5米之内)是否存在行驶障碍物(例如，行人、石块、坑地、台阶等)、预定距离内是否需要改 变行驶状态、轮椅与行驶状态改变点之间的距离等或其任意组合。所述运动数据可以包括但不限于当前时刻轮椅的行驶状态(例如，直行、拐弯、上坡、下坡等)当前时刻轮椅的速度、当前时刻轮椅的加速度、当前时刻轮椅的角速度、当前时刻轮椅的位姿、轮椅已行驶的里程等或其任意组合。在一些实施例中，第一获取模块410可以从轮椅内置的处理引擎112中的存储器220内获取数据，也可以通过网络140访问存储设备150以获取数据。例如，第一获取模块410可以从本地和/或云端获取预存的环境数据。又例如，第一获取模块410可以从本地和/或云端获取轮椅通过当前场景的目标结构参数。在一些实施例中，第一获取模块410在获取上述提及的数据后，可以传输至处理引擎112的其他模块(例如，第一确定模块420)用于后续操作，或通过网络140传输至存储设备150用于存储。
第一确定模块420可以用于基于所述环境数据和/或运动数据，确定对应于所述当前场景的目标结构参数。所述目标结构参数可以是经过优化的轮椅本身的机械参数，以使轮椅平稳安全的通过当前场景。轮椅的结构参数包括但不限于轴距、轮距、底盘高度、座椅倾斜度等或其任意组合。其中，轴距是指分别通过轮椅同一侧面相邻的两车轮中心，并垂直于轮椅纵向剖面的两垂线之间的距离，也可以理解为是轮椅前轮与后轮分别所在的轴(例如，前轴、后轴)之间的距离。轮距是指同轴上(例如，前轴、后轴)左右轮的轮胎对称平面之间在支撑面(水平面)上测定的距离，也可以理解为同轴上(例如，前轴、后轴)左右轮的轮胎之间的距离。底盘高度是指轮椅底盘和轮椅支撑面(水平面)之间的距离，座椅倾斜度是指座椅靠背和座椅坐垫之间的夹角。在一些实施例中，第一确定模块420可 以首先基于环境数据和/或运动数据，确定轮椅通过所处当前场景的行驶状态。例如，轮椅通过当前场景时只需直行、需要转弯、需要上下坡或者任意组合形式的行驶状态。然后基于轮椅的行驶状态，确定所述目标结构参数。
控制模块430可以用于控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。在一些实施例中，所述执行机构包括安装在轮椅上的至少一个电机。所述电机可以接收由控制模块430基于操作520中确定的目标结构参数生成的控制信号，将轮椅的当前结构参数调整为目标结构参数。所述电机可以基于所述控制信号，执行以下至少一个操作：调节轴距的长度；调节轮距的宽度；调节底盘高度；调节座椅倾斜度。
应当理解，图4所示的系统及其模块可以利用各种方式来实现。例如，在一些实施例中，系统及其模块可以通过硬件、软件或者软件和硬件的结合来实现。其中，硬件部分可以利用专用逻辑来实现；软件部分则可以存储在存储器中，由适当的指令执行系统，例如微处理器或者专用设计硬件来执行。本领域技术人员可以理解上述的方法和系统可以使用计算机可执行指令和/或包含在处理器控制代码中来实现，例如在诸如磁盘、CD或DVD-ROM的载体介质、诸如只读存储器(固件)的可编程的存储器或者诸如光学或电子信号载体的数据载体上提供了这样的代码。本申请的系统及其模块不仅可以有诸如超大规模集成电路或门阵列、诸如逻辑芯片、晶体管等的半导体、或者诸如现场可编程门阵列、可编程逻辑设备等的可编程硬件设备的硬件电路实现，也可以用例如由各种类型的处理器所执行的软件实现，还可以由上述硬件电路和软件的结合(例如，固件)来实现。
需要注意的是，以上描述，仅为描述方便，并不能把本申请限制在所举实施例范围之内。可以理解，对于本领域的技术人员来说，在了解该系统的原理后，可以在不背离这一原理的情况下，对实施上述方法和系统的应用领域进行形式和细节上的各种修正和改变。然而，这些变化和修改不脱离本申请的范围。
{{图5}}
图5是根据本发明的一些实施例所示的自适应调节轮椅结构参数的示例性流程图。在一些实施例中，流程500可以通过处理逻辑来执行，该处理逻辑可以包括硬件(例如，电路、专用逻辑、可编程逻辑、微代码等)、软件(运行在处理设备上以执行硬件模拟的指令)等或其任意组合。图5所示的自适应调节轮椅结构参数的流程500中的一个或多个操作可以通过图1所示的智能轮椅控制系统100实现。例如，流程500可以以指令的形式存储在存储设备150中，并由处理引擎112执行调用和/或执行(例如，图2所示的计算设备200的处理器220、图3所示的移动设备300的中央处理器340)。
在510中，可以获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据。操作510可以由第一获取模块410执行。在一些实施例中，所述当前场景可以是所述轮椅在当前时刻所处的一个三维空间，例如，以所述轮椅在当前时刻所处的位置作为坐标原点，在三个坐标轴上(即，x轴、y轴和z轴)正负双向伸展一定的距离(例如，20米)所组成的三维空间可以被指定为轮椅所处的当前场景。所述距离可以是一个预设值，也可以 进行调整，例如，人工调整和/或系统自动调整。在一些实施例中，所述环境数据可以是在所述当前场景中的温度数据、湿度数据、位置数据、地理情况或交通状况等。在一些实施例中，所述环境数据可以是与轮椅运动相关的以上数据，例如，包括但不限于当前场景的地形特征(例如，高山湖泊、树木、人行道、车道、车道线、隔离带、路口交叉点、道路标识、施工地段等)、所述地形特征的数学参数(例如，长、宽、高、曲率、弧长等)、轮椅当前所处位置、预定距离内(例如，5米之内)是否存在行驶障碍物(例如，行人、石块、坑地、台阶等)、预定距离内是否需要改变行驶状态、轮椅与行驶状态改变点之间的距离等或其任意组合。在一些实施例中，所述运动数据可以包括但不限于当前时刻轮椅的行驶状态(例如，直行、拐弯、上坡、下坡等)、当前时刻轮椅的速度、当前时刻轮椅的加速度、当前时刻轮椅的角速度、当前时刻轮椅的位姿、轮椅已行驶的里程等或其任意组合。
在一些实施例中，所述环境数据可以从轮椅内置的处理引擎112中的存储器220内获取，例如，存储器220内已经预先存储了轮椅的运动范围内的地图，较优选的可以是高清地图。所述运动范围可以是一个街区、一个市辖区、一个城市、一个省、一个国家、一个洲和/或全世界。所述高清地图与无人驾驶领域的高清地图的定义相同和/或相似，在此不再赘述。所述高清地图可以包括轮椅运动范围的地理特征数据，例如，地形地貌及其数学参数。第一获取模块410可以通过读取存储单元220内的高清地图，以获取得轮椅运动范围的地理特征数据作为预设环境数据。所述预设环境数据包含的内容可以与所述环境数据相同和/或相似。存储单元220预存的 高清地图可以以一定的时间间隔进行更新，例如，一天。在一些实施例中，所述环境数据可以是通过访问云端服务器，查询轮椅所处当前场景的高清地图来获取。例如，轮椅内置的处理引擎140利用通信端口240通过网络140访问存储设备150以获取存储在其内部的预设环境数据。类似的，存储设备150中存储的高清地图也可以以一定的时间间隔进行更新，例如，一小时，以保证实时性和准确性。在一些实施例中，所述环境数据和/或运动数据可以由位于在轮椅上的一个或一个以上的传感器所捕获。所述一个或一个以上的传感器可以不限于激光雷达、无线电雷达、GPS定位器、超声波传感器、IMU惯性测量传感器、数码相机、光电传感器、速度传感器、加速度传感器等或其任意组合。在一些实施例中，可以利用GPS确定轮椅当前所处位置，利用数码相机/摄像机确定轮椅周围是否存在障碍物或是否需要改变行驶状态，利用激光雷达、雷达传感器以及超声波传感器的单独使用和/或联合使用确定轮椅与障碍物、地形、行驶状态改变点之间的距离和/或障碍物的运动速度(如果有的话)，利用惯性传感器获取轮椅的位姿信息，利用速度传感器获取轮椅的当前速度，利用光电传感器获取轮椅已行驶里程等。所述一个或一个以上的传感器可以是安装轮椅上的传感器，例如，传感器160-1、160-2、160-3等，也可以是轮椅的用户所使用的终端上的传感器，例如，终端120上的内置的GPS定位器、姿态传感器等等。所获取的环境数据和/或运动数据和/或运动数据是实时的，以保证轮椅在行驶过程中安全性、平稳性和舒适性，例如，改变轮椅的结构参数以通过各种不同的道路情况。
在520中，可以基于所述环境数据和/或运动数据，确定对应于所述 当前场景的目标结构参数。操作520可以由第一确定模块420执行。在一些实施例中，所述目标结构参数可以是经过优化的轮椅本身的机械参数，以使轮椅平稳安全的通过当前场景。轮椅的结构参数包括但不限于轴距、轮距、底盘高度、座椅倾斜度等或其任意组合。在一些实施例中，可以首先基于环境数据和/或运动数据，确定轮椅通过所处当前场景的行驶状态。例如，轮椅通过当前场景时只需直行、需要转弯、需要上下坡或者任意组合形式的行驶状态。然后基于轮椅的行驶状态，确定所述目标结构参数。例如，当轮椅高速直行通过所处当前场景时，可以适当调节轴距长度，同时降低底盘高度，增加轮距，以提高轮椅行驶的平稳性，减小翻车的风险。关于确定对应于所述当前场景的目标结构参数的具体描述可以在本说明书的其他地方找到(例如，图6至图8)，在此不再赘述。
在530中，可以控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。操作530可以有控制模块430执行。在一些实施例中，所述执行机构包括安装在轮椅上的至少一个电机，所述电机可以是商业上可用的任意一种电机，例如，直流电机或交流电机，电机的类型不限制本发明方案的实现。所述电机可以接收由控制模块430基于操作520中确定的目标结构参数生成的控制信号，将轮椅的当前结构参数调整为目标结构参数。所述当前结构参数可以是当前时刻轮椅的结构参数。在一些实施例中，所述电机执行以下至少一个操作，以实现上述目的。1)、调节轴距的长度。例如，轮椅可以直行通过当前场景时，获得的目标结构参数中，以超过当前轴距的一个目标轴距运动时，可以使轮椅更加平稳，则电机可以增加轴距的长度到目标轴距。又例如，当轮椅需要转弯通过当前场景时， 以当前轴距继续运动，会在转弯时发生侧翻，则电机可以缩短轴距的长度，以保证轮椅顺利过弯。2)、调节轮距的宽度。例如，轮距的调整可以与轴距的调整相结合，当轴距增长时，轮距也可以相应的增长，当轴距缩短时，轮距也可以相应的缩短，轮距和轴距的比例可以维持在一个值，该数值可以是0.55到0.64之间的任意值，比如0.6。3)、调节底盘高度。例如，当轮椅需要通过一段坑洼路段时，可以增加底盘高度，以提升轮椅的通过性。4)、调节座椅倾斜度。例如，当轮椅通过坡道时，轮椅的使用者会由于坡度的关系发生身体前倾或者后仰，可以调节座椅倾斜度，以提升使用者的舒适性和安全性。应当注意的是，以上举例仅用作说明的目的，任何在所附权利要求范围内的修正和改进，都不脱离本申请的保护范围之类。
在一些实施例中，当轮椅确定通过所处当前场景的目标结构参数后，可以通过网络140将所述当前场景的环境数据及其对应的目标结构参数上传至存储设备150进行存储。所存储的场景的环境数据及其对应的目标结构参数可用于其他轮椅通过同样环境条件时的一个参考。
以上内容描述了本申请和/或一些其他的示例。根据上述内容，本申请还可以做出不同的变形。本申请披露的主题能够以不同的形式和例子所实现，并且本申请可以被应用于大量的应用程序中。后文权利要求中所要求保护的所有应用、修饰以及改变都属于本申请的范围。
{{图6}}
图6是根据本发明的一些实施例所示的确定轮椅目标结构参数的示例性流程图。在一些实施例中，流程600可以由第一确定模块420执行。 在一些实施例中，流程600可以通过处理逻辑来执行，该处理逻辑可以包括硬件(例如，电路、专用逻辑、可编程逻辑、微代码等)、软件(运行在处理设备上以执行硬件模拟的指令)等或其任意组合。图5所示的自适应调节轮椅结构参数的流程600中的一个或多个操作可以通过图1所示的智能轮椅控制系统100实现。例如，流程600可以以指令的形式存储在存储设备150中，并由处理引擎112执行调用和/或执行(例如，图2所示的计算设备200的处理器220、图3所示的移动设备300的中央处理器340)。
在610中，可以基于所述环境数据，确定所述当前场景对应的路况。在一些实施例中，所述路况可以包括直行道、弯道、坡道等或其任意组合。所述环境数据可以表明通过当前场景轮椅所需要经过的路段，以及通过每个路段时轮椅所需的行驶状态，进而判断出当前场景对应的路况。
在620中，可以确定对应与所述路况的空间参数。在一些实施例中，所述空间参数可以是所述路况的物理性质。所述空间参数可以包括但不限于直行道长度、弯道半径、弯道弧长、坡度角、坡面距离、坡面高度等或其任意组合。在一些实施例中，所述空间参数可以通过由内置和/或云端的高清地图中提取得到。高清地图的精度是厘米级的，在对应于一个场景的一副高清地图中，已经包含了该场景中的所有特征数据，例如，人行道或非机动车道的长度、宽度、道路是否发生转弯、转弯半径、是否有上下坡、坡面距离、坡面高度等等，可以直接进行提取。所述空间参数也可以通过所述一个或一个以上的传感器所捕获的环境数据经过计算后得到，例如，通过双目相机所拍摄的图片和/或视频进行立体匹配后得到的物体深度信息来确定。
在630中，可以基于所述空间参数，计算通过所述路况的中间结构参数。在一些实施例中，所述中间结构参数可以是轮椅通过所述路况的结构参数的参考值。例如，对于弯道，轮椅以轴距A进行转弯时，可以通过弯道，但轮椅的稳定性不佳，操作不当时可能具有翻车的风险。所述中间结构参数是一个未经优化后的值，只具备参考的意义。为说明方便，下面以轮椅通过弯道进行举例，来阐述所述中间结构参数的确定过程。对于一个特定的轮椅，它的一些机械参数是确定的，例如，转向轮的转角范围、前悬长度(前轮中心点距离轮椅前端的距离)、整车宽度、转向轴线中心距离等。所述转向轴线是指转向时转向轮的旋转中心轴线。在获取所述空间参数后，可以直接得到弯道的半径以及弯道弧长，则可以通过以下公式计算得到轮椅的轴距。
Figure PCTCN2018104626-appb-000001
其中，R表示弯道半径，L表示轴距，C表示前悬长度，K表示整车的宽度，M表示转向轴中心距离，θ max表示转向轮外轮最大转向角。基于上式进行反向推导即可得到轮椅在过弯时所需的轴距。
在640中，可以判定所述中间结构参数是否超出结构参数范围。在一些实施例中，所述结构参数范围可以是轮椅的机械模型的结构参数的取值范围，该机械模型可以是经过数据统计后对轮椅进行机械建模后得到的。以弯道为例，统计经过多个弯道时轮椅的各种轴距后得出的可以安全稳定通过弯道的轴距的一个取值范围。轮椅以该取值范围外的值通过弯道时可能会发生侧翻等事故或者发生较为明显的颠簸。所述机械模型的建模过程 在现有技术中可以找到，在此不再赘述。在获取所述中间结构参数后，可以判定所述中间结构参数是否位于所述结构参数范围所形成的取值区间内。若所述中间结构参数超出所述结构参数范围所形成的取值区间内，则流程600进行至650，否则，流程600将进行至660。
在650中，所述结构参数范围中更接近于所述中间结构参数的端点值可以被确定为所述目标结构参数。在一些实施例中，若所述中间结构参数不位于所述结构参数范围所形成的取值区间内，则说明若轮椅以所述中间结构参数通过所述路况，轮椅在运动过程中的稳定性及安全性较低，不利于轮椅通过所述路况。在这种情况下，所述结构参数范围中更接近于所述中间结构参数的端点值将被确定为目标结构参数，以保证轮椅在通过所述路况时的安全性和稳定性。
在660中，所述中间结构参数将被确定为所述目标结构参数。在一些实施例中，若所述中间结构参数位于所述结构参数范围所形成的取值区间内，则说明若轮椅以所述中间结构参数通过所述路况，可以安全稳定的通过。在这种情况下，所述中间结构参数将被直接确定为所述目标结构参数，在后续过程中(例如，流程500的530中)，轮椅的当前结构参数将被调整为所述目标结构参数。
以上内容描述了本申请和/或一些其他的示例。根据上述内容，本申请还可以做出不同的变形。本申请披露的主题能够以不同的形式和例子所实现，并且本申请可以被应用于大量的应用程序中。后文权利要求中所要求保护的所有应用、修饰以及改变都属于本申请的范围。
{{图7}}
图7是根据本发明的一些实施例所示的确定轮椅目标结构参数的示例性流程图。在一些实施例中，流程700可以由第一确定模块420执行。在一些实施例中，流程700可以通过处理逻辑来执行，该处理逻辑可以包括硬件(例如，电路、专用逻辑、可编程逻辑、微代码等)、软件(运行在处理设备上以执行硬件模拟的指令)等或其任意组合。图7所示的用于获取智能轮椅模型的流程700中的一个或多个操作可以通过图1所示的智能轮椅系统100实现。例如，流程700可以以指令的形式存储在存储设备150中，并由处理引擎112执行调用和/或执行(例如，图2所示的计算设备200的处理器220、图3所示的移动设备300的中央处理器340)。
在710中，可以获取对应于所述环境数据的预设结构参数。所述预设结构参数可以是预先存储在本地或服务器上的数据。在一些实施例中，预设结构参数可以与场景的位置、路况等环境数据对应存储。基于当前场景的位置或路况等环境数据可以从本地或服务器上直接获取对应的预设结构参数。在一些实施例中，所述预设结构参数可以是一个或一个以上的轮椅通过所述当前场景时所使用的目标结构参数。对于某一特定场景，可以有一个或一个以上的轮椅已经以对应于该场景的结构参数通过。该结构参数可以是基于该场景的环境数据计算得到(例如，基于流程600得到)。在获得轮椅的结构参数后，通过该场景的轮椅可以将该场景及其对应的结构参数上传并存储，也可以存储在本地存储器中。当某一轮椅处于该场景时(该轮椅可以是从未处于该场景，或已经通过过该场景)，可以直接通过网 络140获取对应于该场景的结构参数作为预设结构参数，也可以通过查询本地存储器以获取通过该场景的结构参数作为预设结构参数。
在720中，可以将所述预设结构参数确定为所述目标结构参数。在获取所述预设结构参数后，第一确定模块420可以直接将所述预设结构参数确定为所述目标结构参数，控制模块430可以基于所述目标结构参数生成控制信号以控制电机对轮椅的结构参数进行调整。
以上内容描述了本申请和/或一些其他的示例。根据上述内容，本申请还可以做出不同的变形。本申请披露的主题能够以不同的形式和例子所实现，并且本申请可以被应用于大量的应用程序中。后文权利要求中所要求保护的所有应用、修饰以及改变都属于本申请的范围。
{{图8}}
图8是根据本发明的一些实施例所示的示例性处理设备800的框图。如图所示，处理设备800可以包括第二获取模块810、第二确定模块820和传输模块830。处理设备800可以实现在位于轮椅110外部的服务器130中(例如，云端服务器)。
第二获取模块810可以获取轮椅所处当前场景的环境数据。在一些实施例中，轮椅所处当前场景的环境数据可以查询预存储在轮椅内部存储器(例如，存储单元220)和/或存储在存储设备150中的高清地图来获取，或者由位于轮椅上的一个或一个以上传感器所捕获。
第二确定模块820可以确定对应于所述环境数据的轮椅结构参数。所述轮椅结构参数可以是轮椅通过所处场景的目标结构参数。在一些实施 例中，第二确定模块820可以基于所获取的环境数据，计算所述轮椅结构参数。第二确定模块820可以基于所述环境数据，确定轮椅所述当前场景对应的路况，并获取对应于所述路况的空间参数，然后利用所述空间参数，计算通过所述路况的中间结构参数。在确定中间结构参数后，第二确定模块820可以将中间结构参数与结构参数范围进行比较。若所述中间结构参数位于所述结构参数范围所形成的取值区间内，则将中间结构参数确定为轮椅所处当前场景对应的目标结构参数。否则，将结构参数范围中更接近于中间结构参数的端点值确定为轮椅所处当前场景对应的目标结构参数。
在一些实施例中，第二确定模块820可以查询存储设备(例如，存储设备150)，获取与轮椅所处当前场景对应的结构参数。所述存储设备存储有至少一组场景-结构参数数据，所述场景-结构参数数据包括至少一个场景及其所对应的轮椅结构参数。所述场景及其所对应的轮椅结构参数可以由通过该场景的轮椅上传至存储设备150进行存储的。
在一些实施例中，第二确定模块820可以将所述环境数据输入至结构参数确定模型中。所述结构参数确定模型可以是现有机器学习模型中的一种或一种以上的组合，包括但不限于决策树、随机森林、逻辑回归、支持向量机、朴素贝叶斯、K最近邻算法、K均值算法、Adaboost、神经网络、马尔可夫模型等或其任意组合。在一些实施例中，所述结构参数确定模型可以基于多个场景及其对应的轮椅结构参数样本对训练得到。所述场景及其对应的轮椅结构参数样本对可以包括一个场景以及轮椅通过该场景时的目标结构参数。在将场景的环境输入后，第二确定模块820可以直接基于所述结构参数确定模型，确定轮椅的结构参数。
传输模块830可以发送所述轮椅结构参数所述轮椅的至少一个处理器。在一些实施例中，传输模块830可以通过网络140发送至所述轮椅的至少一个处理器，例如，内置在轮椅上的处理引擎140的处理器210。
应当理解，图8所示的系统及其模块可以利用各种方式来实现。例如，在一些实施例中，系统及其模块可以通过硬件、软件或者软件和硬件的结合来实现。其中，硬件部分可以利用专用逻辑来实现；软件部分则可以存储在存储器中，由适当的指令执行系统，例如微处理器或者专用设计硬件来执行。本领域技术人员可以理解上述的方法和系统可以使用计算机可执行指令和/或包含在处理器控制代码中来实现，例如在诸如磁盘、CD或DVD-ROM的载体介质、诸如只读存储器(固件)的可编程的存储器或者诸如光学或电子信号载体的数据载体上提供了这样的代码。本申请的系统及其模块不仅可以有诸如超大规模集成电路或门阵列、诸如逻辑芯片、晶体管等的半导体、或者诸如现场可编程门阵列、可编程逻辑设备等的可编程硬件设备的硬件电路实现，也可以用例如由各种类型的处理器所执行的软件实现，还可以由上述硬件电路和软件的结合(例如，固件)来实现。
需要注意的是，以上描述，仅为描述方便，并不能把本申请限制在所举实施例范围之内。可以理解，对于本领域的技术人员来说，在了解该系统的原理后，可以在不背离这一原理的情况下，对实施上述方法和系统的应用领域进行形式和细节上的各种修正和改变。然而，这些变化和修改不脱离本申请的范围。
{{图9}}
图9是根据本发明的一些实施例所示的确定轮椅目标结构参数的示例性流程图。在一些实施例中，流程900可以通过处理逻辑来执行，该处理逻辑可以包括硬件(例如，电路、专用逻辑、可编程逻辑、微代码等)、软件(运行在处理设备上以执行硬件模拟的指令)等或其任意组合。图8所示的用于获取待测目标的干扰对象集的流程900中的一个或多个操作可以通过图1所示的智能轮椅系统100实现。例如，流程800可以以指令的形式存储在存储设备150中，并由处理引擎112执行调用和/或执行(例如，图2所示的计算设备200的处理器220、图3所示的移动设备300的中央处理器340)。
在910中，可以获取轮椅所处当前场景的环境数据。操作910可以由第二获取模块810执行。轮椅所述当前场景的环境数据可以是轮椅获取后上传的，也可以是轮椅仅上传所处场景的位置，第二获取模块根据所述位置信息查询存储在本地和/或存储在存储设备150中的高清地图来获取。所述环境数据的内容和获取方式与和操作510中的描述类似，在此不再赘述。
在920中，可以确定对应于所述环境数据的轮椅结构参数。操作920可以由第二确定模块820执行。在一些实施例中，所述轮椅结构参数可以是轮椅通过所处场景的目标结构参数。在一些实施例中，可以基于所述环境数据，确定轮椅所述当前场景对应的路况。所述路况可以包括直行道、弯道、坡道等或其任意组合。在获取对应于当前场景的路况后，可以确定 对应于所述路况的空间参数。所述空间参数可以是所述路况的物理性质。所述空间参数可以包括但不限于直行道长度、弯道半径、弯道弧长、坡度角、坡面距离、坡面高度等或其任意组合。所述空间参数可以通过由内置和/或云端的高清地图中提取得到，也可以通过所述一个或一个以上的传感器所捕获的环境数据经过计算后得到。然后，可以基于所述空间参数，计算通过所述路况的中间结构参数，并将中间结构参数与结构参数范围进行比较，若满足条件，例如，所述中间结构参数位于所述结构参数范围所形成的取值区间内，则将中间结构参数确定为轮椅所处当前场景对应的目标结构参数。否则，将结构参数范围中更接近于中间结构参数的端点值确定为轮椅所处当前场景对应的目标结构参数。关于确定目标结构参数的描述可以参考本发明书其他部分，例如，图6部分的描述。
在一些实施例中，可以查询存储设备(例如，存储设备150)，获取与轮椅所处当前场景对应的结构参数。所述存储设备存储有至少一组场景-结构参数数据，所述场景-结构参数数据包括至少一个场景的环境数据及其所对应的轮椅结构参数。对于所述至少一个场景，可以统计并记录一个或多个轮椅通过时所使用的结构参数，进而形成至少一组场景-结构参数数据。该结构参数可以是基于该场景的环境数据计算得到(例如，基于流程600得到)。在获得轮椅的结构参数后，通过该场景的轮椅可以将该场景的环境数据及其对应的结构参数上传并存储，例如，存储在存储设备150中。当获取某一轮椅所处场景的环境数据后，可以查询存储设备150中的数据，获取所处场景所对应的结构参数。
在一些实施例中，可以将所述环境数据输入至结构参数确定模型中。 所述结构参数确定模型可以是现有机器学习模型中的一种或一种以上的组合，包括但不限于决策树、随机森林、逻辑回归、支持向量机、朴素贝叶斯、K最近邻算法、K均值算法、Adaboost、神经网络、马尔可夫模型等或其任意组合。在一些实施例中，所述结构参数确定模型可以基于多个场景的环境数据及其对应的轮椅结构参数样本对训练得到。所述场景的环境数据及其对应的轮椅结构参数样本对可以包括一个场景的环境数据以及轮椅通过该场景时的目标结构参数。在训练之前，所述结构参数确定模型具有多个初始模型参数，例如，学习率，超参数等。所述初始模型参数可以是系统的默认值，也可以根据实际应用情况进行调整修改。所述初始模型的训练过程可以从现有技术中找到，在此不在赘述。当满足某一预设条件时，例如，训练样本数达到预定的数量，模型的预测正确率大于某一预定准确率阈值，或损失函数(Loss Function)的值小于某一预设值，训练过程将停止。训练完成后的结构参数确定模型，可以用于确定通过一个场景时轮椅的结构参数。在一些实施例中，所述结构参数确定模型可以在经过一定时间间隔后进行更新，例如，一天、一星期等。可以利用在时间间隔内新产生的场景-结构参数对来对结构参数确定模型进行更新，例如，由通过某一场景的轮椅上传的场景-结构参数对和/或由计算得到的场景-结构参数对。在将场景的环境输入后，可以基于所述结构参数确定模型，确定轮椅的结构参数。所述结构参数确定模型可以直接输出对应于通过场景的轮椅的结构参数。
在930中，可以发送所述轮椅结构参数所述轮椅的至少一个处理器。操作930可以由传输模块830执行。在一些实施例中，所述轮椅结构参数 可以通过网络140发送至所述轮椅的至少一个处理器，例如，内置在轮椅上的处理引擎140的处理器210。所述至少一个处理器可以基于接收到的轮椅结构参数，生成控制信号并发送至轮椅上的执行设备，由执行设备基于所述控制信号调节轮椅的结构参数以通过所述场景。
需要注意的是，以上描述，仅为描述方便，并不能把本申请限制在所举实施例范围之内。可以理解，对于本领域的技术人员来说，在了解该系统的原理后，可以在不背离这一原理的情况下，对实施上述方法和系统的应用领域进行形式和细节上的各种修正和改变。
与现有技术相比，本申请以上各实施例可能带来的有益效果包括但不限于：
(1)、可以根据轮椅当前所处场景自动调节轮椅的结构参数，提升轮椅在行驶过程中的安全性、稳定性和使用者的舒适性。
(2)、根据轮椅在行驶过程中传感器检测到的数据，根据不同的场景对轮椅的结构参数做出不同的调节，以适应各种不同的行驶路况。
需要说明的是，不同实施例可能产生的有益效果不同，在不同的实施例里，可能产生的有益效果可以是以上任意一种或几种的组合，也可以是其他任何可能获得的有益效果。
以上内容描述了本申请和/或一些其他的示例。根据上述内容，本申请还可以做出不同的变形。本申请披露的主题能够以不同的形式和例子所实现，并且本申请可以被应用于大量的应用程序中。后文权利要求中所要求保护的所有应用、修饰以及改变都属于本申请的范围。
同时，本申请使用了特定词语来描述本申请的实施例。如“一个实施 例”、“一实施例”、和/或“一些实施例”意指与本申请至少一个实施例相关的某一特征、结构或特点。因此，应强调并注意的是，本说明书中在不同位置两次或多次提及的“一实施例”或“一个实施例”或“一替代性实施例”并不一定是指同一实施例。此外，本申请的一个或多个实施例中的某些特征、结构或特点可以进行适当的组合。
本领域技术人员能够理解，本申请所披露的内容可以出现多种变型和改进。例如，以上所描述的不同系统组件都是通过硬件设备所实现的，但是也可能只通过软件的解决方案得以实现。例如：在现有的服务器上安装系统。此外，这里所披露的位置信息的提供可能是通过一个固件、固件/软件的组合、固件/硬件的组合或硬件/固件/软件的组合得以实现。
所有软件或其中的一部分有时可能会通过网络进行通信，如互联网或其他通信网络。此类通信能够将软件从一个计算机设备或处理器加载到另一个。例如：从智能轮椅系统的一个管理服务器或主机计算机加载至一个计算机环境的硬件平台，或其他实现系统的计算机环境，或与提供确定轮椅目标结构参数所需要的信息相关的类似功能的系统。因此，另一种能够传递软件元素的介质也可以被用作局部设备之间的物理连接，例如光波、电波、电磁波等，通过电缆、光缆或者空气实现传播。用来载波的物理介质如电缆、无线连接或光缆等类似设备，也可以被认为是承载软件的介质。在这里的用法除非限制了有形的“储存”介质，其他表示计算机或机器“可读介质”的术语都表示在处理器执行任何指令的过程中参与的介质。
本申请各部分操作所需的计算机程序编码可以用任意一种或多种程序语言编写，包括面向对象编程语言如Java、Scala、Smalltalk、Eiffel、JADE、 Emerald、C++、C#、VB.NET、Python等，常规程序化编程语言如C语言、Visual Basic、Fortran 2003、Perl、COBOL 2002、PHP、ABAP，动态编程语言如Python、Ruby和Groovy，或其他编程语言等。该程序编码可以完全在用户计算机上运行、或作为独立的软件包在用户计算机上运行、或部分在用户计算机上运行部分在远程计算机运行、或完全在远程计算机或服务器上运行。在后种情况下，远程计算机可以通过任何网络形式与用户计算机连接，例如，局域网(LAN)或广域网(WAN)，或连接至外部计算机(例如通过因特网)，或在云计算环境中，或作为服务使用如软件即服务(SaaS)。
此外，除非权利要求中明确说明，本申请所述处理元素和序列的顺序、数字字母的使用、或其他名称的使用，并非用于限定本申请流程和方法的顺序。尽管上述披露中通过各种示例讨论了一些目前认为有用的发明实施例，但应当理解的是，该类细节仅起到说明的目的，附加的权利要求并不仅限于披露的实施例，相反，权利要求旨在覆盖所有符合本申请实施例实质和范围的修正和等价组合。例如，虽然以上所描述的系统组件可以通过硬件设备实现，但是也可以只通过软件的解决方案得以实现，如在现有的服务器或移动设备上安装所描述的系统。
同理，应当注意的是，为了简化本申请披露的表述，从而帮助对一个或多个发明实施例的理解，前文对本申请实施例的描述中，有时会将多种特征归并至一个实施例、附图或对其的描述中。但是，这种披露方法并不意味着本申请对象所需要的特征比权利要求中提及的特征多。实际上，实施例的特征要少于上述披露的单个实施例的全部特征。
一些实施例中使用了描述属性、数量的数字，应当理解的是，此类用于实施例描述的数字，在一些示例中使用了修饰词“大约”、“近似”或“大体上”来修饰。除非另外说明，“大约”、“近似”或“大体上”表明所述数字允许有±20％的变化。相应地，在一些实施例中，说明书和权利要求中使用的数值参数均为近似值，该近似值根据个别实施例所需特点可以发生改变。在一些实施例中，数值参数应考虑规定的有效数位并采用一般位数保留的方法。尽管本申请一些实施例中用于确认其范围广度的数值域和参数为近似值，在具体实施例中，此类数值的设定在可行范围内尽可能精确。
针对本申请引用的每个专利、专利申请、专利申请公开物和其他材料，如文章、书籍、说明书、出版物、文档、物件等，特将其全部内容并入本申请作为参考。与本申请内容不一致或产生冲突的申请历史文件除外，对本申请权利要求最广范围有限制的文件(当前或之后附加于本申请中的)也除外。需要说明的是，如果本申请附属材料中的描述、定义、和/或术语的使用与本申请所述内容有不一致或冲突的地方，以本申请的描述、定义和/或术语的使用为准。
最后，应当理解的是，本申请中所述实施例仅用以说明本申请实施例的原则。其他的变形也可能属于本申请的范围。因此，作为示例而非限制，本申请实施例的替代配置可视为与本申请的教导一致。相应地，本申请的实施例不限于本申请明确介绍和描述的实施例。

Claims (21)

  1. 一种轮椅结构参数自适应调节方法，由至少一个处理器实现，其特征在于，包括：
    获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据；
    基于所述环境数据和/或运动数据，确定对应于所述当前场景的目标结构参数；以及
    控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。
  2. 根据权利要求1所述的方法，其特征在于，所述获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据，包括：
    获取关于所述当前场景的预设环境数据；
    或者由位于在轮椅上的一个或一个以上的传感器所捕获的轮椅所处当前场景的环境数据和/或所述运动数据。
  3. 根据权利要求1所述的方法，其特征在于，所述基于所述环境数据，确定对应于所述当前场景的目标结构参数，包括：
    基于所述环境数据，确定所述当前场景对应的路况；所述路况包括以下路况中的至少一个：直行道、弯道和坡道；
    确定对应于所述路况的空间参数；
    基于所述空间参数，确定通过所述路况的目标结构参数。
  4. 根据权利要求3所述的方法，其特征在于，所述路况的空间参数，包括 以下至少一个：直行道长度、弯道半径、弯道弧长、坡度角、坡面距离和坡道高度。
  5. 根据权利要求3所述的方法，其特征在于，所述基于所述空间参数，确定通过所述路况的目标结构参数，包括：
    基于所述空间参数，计算通过所述路况的中间结构参数；
    判断所述中间结构参数是否超出结构参数范围；
    响应于所述中间结构参数超出结构参数范围的判定，将所述结构参数范围中更接近于所述中间结构参数的端点值确定为所述目标结构参数。
  6. 根据权利要求3所述的方法，其特征在于，所述基于所述空间参数，确定通过所述路况的目标结构参数，包括：
    基于所述空间参数，计算通过所述路况的中间结构参数；
    判断所述中间结构参数是否超出结构参数范围；
    响应于所述中间结构参数不超过所述结构参数范围的判定，将所述中间结构参数确定为所述目标结构参数。
  7. 根据权利要求1所述的方法，其特征在于，所述基于所述环境数据，确定对应于所述当前场景的目标结构参数，包括：
    获取对应于所述环境数据的预设结构参数；以及
    将所述预设结构参数确定为所述目标结构参数。
  8. 根据权利要求1所述的方法，其特征在于，所述结构参数包括以下至少一个：轴距、轮距、底盘高度和座椅倾斜度。
  9. 根据权利要求8所述的方法，其特征在于，所述执行结构包括至少一个电机，所述电机用于接收所述至少一个处理器的控制信号以执行以下至少一个操作：
    调节所述轴距的长度；
    调节所述轮距的宽度；
    调节所述底盘高度；以及
    调节所述座椅倾斜度。
  10. 根据权利要求1所述的方法，其特征在于，所述方法进一步包括：
    上传所述当前场景的环境数据及其所对应的目标结构参数。
  11. 一种轮椅结构参数自适应调节系统，其特征在于，所述系统包括至少一个处理器和至少一个存储设备，所述存储设备用于存储指令，当所述至少一个处理器执行所述指令时，实现以下操作：
    获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据；
    基于所述环境数据和/或运动数据，确定对应于所述当前场景的目标结构参数；以及
    控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。
  12. 一种轮椅结构参数自适应调节系统，其特征在于，所述系统包括第一获取模块、第一确定模块和控制模块；
    所述第一获取模块，用于获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据；
    所述第一确定模块，用于基于所述环境数据和/或运动数据，确定对应于所述当前场景的目标结构参数；
    所述控制模块，用于控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。
  13. 一种计算机可读存储介质，其特征在于，所述存储介质存储计算机程序，当计算机读取存储介质中的计算机程序后，计算机运行如下操作：
    获取轮椅所处当前场景的环境数据和/或所述轮椅的运动数据；
    基于所述环境数据和/或运动数据，确定对应于所述当前场景的目标结构参数；以及
    控制轮椅上的执行机构以调节轮椅的当前结构参数至所述目标结构参数。
  14. 一种用于轮椅结构参数自适应调节的方法，由至少一个处理器实现，其特征在于，包括：
    获取所述轮椅当前所处场景的环境数据；
    确定对应与于所述环境数据的轮椅结构参数；以及
    发送所述轮椅结构参数至所述轮椅上的至少一个处理器。
  15. 根据权利要求14所述的方法，其特征在于，所述方法进一步包括：
    接收并存储所述轮椅上的至少一个处理器发送的所述轮椅所处当前场景的环境数据及其对应的轮椅结构参数至所述存储设备。
  16. 根据权利要求14所述的方法，其特征在于，所述确定对应与于所述环境数据的轮椅结构参数，包括：
    基于所述环境数据，确定所述当前场景对应的路况；所述路况包括以下路况中的至少一个：直行道、弯道和坡道；
    确定对应于所述路况的空间参数；
    基于所述空间参数，确定通过所述路况的轮椅结构参数。
  17. 根据权利要求14所述的方法，其特征在于，所述确定对应与于所述环境数据的轮椅结构参数，包括：
    查询存储设备，获取与轮椅所处当前场景的环境数据对应的结构参数；
    所述存储设备存储有至少一组场景-结构参数数据；所述场景-结构参数数据包括至少一个场景的环境数据及其所对应的轮椅结构参数。
  18. 根据权利要求14所述的方法，其特征在于，所述确定对应与于所述环境数据的轮椅结构参数，包括：
    将所述环境数据输入至结构参数确定模型，其中，所述结构参数确定 模型为机器学习模型，基于多个场景的环境数据及其对应的轮椅结构参数样本对进行训练后得到；以及
    基于所述结构参数确定模型，确定轮椅的结构参数。
  19. 一种用于轮椅结构参数自适应调节的系统，其特征在于，所述系统包括至少一个处理器和至少一个存储设备，所述存储设备用于存储指令，当所述至少一个处理器执行所述指令时，实现以下操作：
    获取所述轮椅当前所处场景的环境数据；
    确定对应与于所述环境数据的轮椅结构参数；以及
    发送所述轮椅结构参数至所述轮椅上的至少一个处理器。
  20. 一种用于轮椅结构参数自适应调节的系统，所述系统包括第二获取模块、第二确定模块和传输模块；
    所述第二获取模块，用于获取所述轮椅当前所处场景的环境数据；
    所述第二确定模块，用于确定对应与于所述环境数据的轮椅结构参数；
    所述传输模块，用于发送所述轮椅结构参数至所述轮椅上的至少一个处理器。
  21. 一种计算机可读存储介质，其特征在于，所述存储介质存储计算机程序，当计算机读取存储介质中的计算机程序后，计算机运行如下操作：
    获取所述轮椅当前所处场景的环境数据；
    确定对应与于所述环境数据的轮椅结构参数；以及
    发送所述轮椅结构参数至所述轮椅上的至少一个处理器。
PCT/CN2018/104626 2018-09-07 2018-09-07 一种轮椅结构参数自适应调节方法、系统及存储介质 WO2020047847A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201880095804.0A CN112566603B (zh) 2018-09-07 2018-09-07 一种轮椅结构参数自适应调节方法、系统及存储介质
PCT/CN2018/104626 WO2020047847A1 (zh) 2018-09-07 2018-09-07 一种轮椅结构参数自适应调节方法、系统及存储介质

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2018/104626 WO2020047847A1 (zh) 2018-09-07 2018-09-07 一种轮椅结构参数自适应调节方法、系统及存储介质

Publications (1)

Publication Number Publication Date
WO2020047847A1 true WO2020047847A1 (zh) 2020-03-12

Family

ID=69722120

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/104626 WO2020047847A1 (zh) 2018-09-07 2018-09-07 一种轮椅结构参数自适应调节方法、系统及存储介质

Country Status (2)

Country Link
CN (1) CN112566603B (zh)
WO (1) WO2020047847A1 (zh)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113018018A (zh) * 2021-03-01 2021-06-25 广州希科医疗器械科技有限公司 轮椅电机的控制方法、系统及装置和轮椅
CN114376811A (zh) * 2021-12-13 2022-04-22 深圳市优必选科技股份有限公司 轮椅及其控制方法、装置及计算机可读存储介质
US11628105B2 (en) 2020-06-25 2023-04-18 Toyota Motor North America, Inc. Powered wheelchairs and methods for maintaining a powered wheelchair in a pre-selected position

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113777961B (zh) * 2021-08-06 2023-05-23 季华实验室 轮椅护理床控制方法、系统及计算机可读存储介质
CN117234115B (zh) * 2023-11-15 2024-02-02 深圳安培时代数字能源科技有限公司 电动轮椅的控制方法及相关装置

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102641190A (zh) * 2012-05-15 2012-08-22 山东理工大学 一种可以自动适应路况的轮椅行进机构
CN106029034A (zh) * 2014-01-30 2016-10-12 联邦高等教育系统匹兹堡大学 座椅功能监控和指导系统
CN106038098A (zh) * 2016-06-24 2016-10-26 张学海 基于电脑处理器的电动轮椅的控制系统及电动轮椅
US20170189250A1 (en) * 2013-12-05 2017-07-06 Now Technologies Zrt. Personal Vehicle, And Control Apparatus And Control Method Therefore
US20180042797A1 (en) * 2016-08-10 2018-02-15 Max Mobility, Llc Self-balancing wheelchair
CN108294869A (zh) * 2018-01-08 2018-07-20 深圳市易成自动驾驶技术有限公司北京分公司 智能轮椅警示方法、智能轮椅及计算机可读存储介质

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4375700B2 (ja) * 2001-07-23 2009-12-02 新東工業株式会社 全方向移動型電動車椅子のジョイスティックの操作制限システム
US7204328B2 (en) * 2004-06-21 2007-04-17 Lopresti Edmund F Power apparatus for wheelchairs
CN102631265B (zh) * 2012-05-11 2014-06-18 重庆大学 一种智能轮椅的嵌入式控制系统
US9835456B1 (en) * 2016-05-10 2017-12-05 Fujitsu Limited Wheelchair assistance system
CA2985450A1 (en) * 2016-11-14 2018-05-14 Redliner Inc. Automatically recommending changes to wheelchair setting based on usage data
CN106933157A (zh) * 2017-04-20 2017-07-07 武汉理工大学 一种轮椅安全监测装置及监测方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102641190A (zh) * 2012-05-15 2012-08-22 山东理工大学 一种可以自动适应路况的轮椅行进机构
US20170189250A1 (en) * 2013-12-05 2017-07-06 Now Technologies Zrt. Personal Vehicle, And Control Apparatus And Control Method Therefore
CN106029034A (zh) * 2014-01-30 2016-10-12 联邦高等教育系统匹兹堡大学 座椅功能监控和指导系统
CN106038098A (zh) * 2016-06-24 2016-10-26 张学海 基于电脑处理器的电动轮椅的控制系统及电动轮椅
US20180042797A1 (en) * 2016-08-10 2018-02-15 Max Mobility, Llc Self-balancing wheelchair
CN108294869A (zh) * 2018-01-08 2018-07-20 深圳市易成自动驾驶技术有限公司北京分公司 智能轮椅警示方法、智能轮椅及计算机可读存储介质

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11628105B2 (en) 2020-06-25 2023-04-18 Toyota Motor North America, Inc. Powered wheelchairs and methods for maintaining a powered wheelchair in a pre-selected position
CN113018018A (zh) * 2021-03-01 2021-06-25 广州希科医疗器械科技有限公司 轮椅电机的控制方法、系统及装置和轮椅
CN114376811A (zh) * 2021-12-13 2022-04-22 深圳市优必选科技股份有限公司 轮椅及其控制方法、装置及计算机可读存储介质
CN114376811B (zh) * 2021-12-13 2024-02-13 深圳市优必选科技股份有限公司 轮椅及其控制方法、装置及计算机可读存储介质

Also Published As

Publication number Publication date
CN112566603A (zh) 2021-03-26
CN112566603B (zh) 2023-04-11

Similar Documents

Publication Publication Date Title
WO2020047847A1 (zh) 一种轮椅结构参数自适应调节方法、系统及存储介质
US11320836B2 (en) Algorithm and infrastructure for robust and efficient vehicle localization
WO2021013193A1 (zh) 一种交通灯的识别方法及装置
US20220229436A1 (en) Real-time lane change selection for autonomous vehicles
US10474157B2 (en) Data-based control error detection and parameter compensation system
US11364931B2 (en) Lidar localization using RNN and LSTM for temporal smoothness in autonomous driving vehicles
US20210287438A1 (en) Localization method and apparatus of displaying virtual object in augmented reality
US20190273856A1 (en) Image processing device, image processing method, and program
WO2020154972A1 (en) Lidar localization using 3d cnn network for solution inference in autonomous driving vehicles
WO2020154970A1 (en) Deep learning–based feature extraction for lidar localization of autonomous driving vehicles
CN112740268B (zh) 目标检测方法和装置
CN110531750A (zh) 用于自动驾驶车辆的pid嵌入式lqr
US20200209872A1 (en) St-graph learning based decision for autonomous driving vehicle
US20180364657A1 (en) Method and system for determining optimal coefficients of controllers for autonomous driving vehicles
CN108891417A (zh) 用于操作自动驾驶车辆的方法及数据处理系统
WO2021036862A1 (zh) 车辆控制方法、相关设备及计算机存储介质
EP4246440A2 (en) Method and apparatus for localization based on images and map data
WO2022247203A1 (zh) 自动驾驶车辆的控制方法、装置、设备以及存储介质
WO2020062030A1 (en) A spiral path based three-point turn planning for autonomous driving vehicles
CN114882464B (zh) 多任务模型训练方法、多任务处理方法、装置及车辆
WO2022052881A1 (zh) 一种构建地图的方法及计算设备
WO2020191711A1 (en) A camera-based low-cost lateral position calibration method for level-3 autonomous vehicles
WO2021129073A1 (zh) 一种测距方法以及测距装置
EP2991358A2 (en) Communication of cloud-based content to a driver
US20220198714A1 (en) Camera to camera calibration

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18932773

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 18932773

Country of ref document: EP

Kind code of ref document: A1

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205 DATED 01-12-2021)

122 Ep: pct application non-entry in european phase

Ref document number: 18932773

Country of ref document: EP

Kind code of ref document: A1