WO2019126957A1 - 端云结合定位方法、装置及电子设备、计算机程序产品 - Google Patents

端云结合定位方法、装置及电子设备、计算机程序产品 Download PDF

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Publication number
WO2019126957A1
WO2019126957A1 PCT/CN2017/118348 CN2017118348W WO2019126957A1 WO 2019126957 A1 WO2019126957 A1 WO 2019126957A1 CN 2017118348 W CN2017118348 W CN 2017118348W WO 2019126957 A1 WO2019126957 A1 WO 2019126957A1
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Prior art keywords
positioning
data
mode
terminal
cloud
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PCT/CN2017/118348
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English (en)
French (fr)
Inventor
林义闽
廉士国
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深圳前海达闼云端智能科技有限公司
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Application filed by 深圳前海达闼云端智能科技有限公司 filed Critical 深圳前海达闼云端智能科技有限公司
Priority to PCT/CN2017/118348 priority Critical patent/WO2019126957A1/zh
Priority to CN201780002723.7A priority patent/CN108235809B/zh
Publication of WO2019126957A1 publication Critical patent/WO2019126957A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/52—Network services specially adapted for the location of the user terminal

Definitions

  • the present application relates to a positioning technology, and in particular, to a terminal cloud combining positioning method, device, electronic device, and computer program product.
  • the intelligent robot terminal positioning processing ability is weak, and the application scenario is very limited, so that the existing robot can only be active in specific occasions, such as stations, offices, restaurants, museums, and the like.
  • a method and device for locating the end cloud are provided, and an electronic device and a computer program product are provided, which can fully utilize the advantages of the cloud and the terminal to achieve more effective positioning.
  • a positioning method including the following steps:
  • the decision instruction is calculated according to the original data required by the first positioning data and the second positioning mode.
  • a positioning method including the following steps:
  • the first positioning data is obtained by using the first positioning manner
  • a positioning apparatus including:
  • a terminal positioning module configured to perform positioning by using the first positioning manner, to obtain first positioning data
  • a terminal sending module configured to upload the first positioning data and the original data required by the second positioning mode to the cloud
  • the terminal receiving module is configured to receive a decision instruction sent by the cloud, where the decision instruction is calculated according to the original data required by the first positioning data and the second positioning mode.
  • a positioning apparatus including:
  • the cloud receiving module is configured to receive the first positioning data uploaded by the terminal and the original data required by the second positioning mode; the first positioning data is obtained by using the first positioning manner;
  • a cloud positioning module configured to perform positioning by using a second positioning manner according to the original data required by the second positioning manner, to obtain second positioning data
  • a fusion module configured to generate a decision instruction according to the first positioning data and the second positioning data
  • the cloud sending module is configured to send the decision instruction to the terminal.
  • an electronic device comprising: a display, a memory, one or more processors; and one or more modules, the one or more modules being stored In the memory, and configured to be executed by the one or more processors, the one or more modules include instructions for performing the various steps in the positioning method of the first aspect of the embodiments of the present application.
  • a computer program product for encoding instructions for performing a process, the process comprising the positioning method of the first aspect of the embodiments of the present application .
  • a part of the positioning mode can be deployed to the terminal, and a part of the positioning mode is deployed in the cloud, thereby fully utilizing the real-time processing capability of the terminal and the computing capability of the cloud, thereby It can ensure the accuracy of positioning while reducing the resource consumption of the terminal.
  • FIG. 1 is a schematic flowchart diagram of implementation of a terminal side positioning method in an embodiment of the present application
  • FIG. 2 is a schematic flowchart showing the implementation of the cloud side positioning method in the embodiment of the present application
  • FIG. 3 is a schematic structural diagram of a terminal side positioning device in an embodiment of the present application.
  • FIG. 4 is a schematic structural diagram of a cloud side positioning device in the embodiment of the present application.
  • FIG. 5 is a schematic diagram showing a pedestrian positioning process according to an embodiment of the present application.
  • FIG. 6 is a schematic diagram showing a positioning process of an intelligent logistics vehicle and a cloud server in the embodiment of the present application.
  • positioning technology can be divided into two categories: absolute and relative positioning.
  • absolute positioning For example, vSLAM relocation, GPS, WIFI, 4G and other wireless positioning technologies are absolute positioning.
  • Positioning technologies such as IMU and VIO are relatively positioned. Solving the robot's movement problem by relying on any one of the positioning technologies alone, this application combines these two types of positioning methods - global absolute positioning, local relative positioning, and can be based on algorithm complexity and positioning frequency. They are deployed in the cloud and terminals respectively to form an effective positioning system.
  • the embodiment of the present application describes the positioning method from the terminal side.
  • FIG. 1 is a schematic flowchart of a method for performing a terminal-side positioning method in an embodiment of the present application. As shown in the figure, the positioning method may include the following steps:
  • Step 101 Perform positioning by using the first positioning manner to obtain first positioning data; and obtain original data required by the second positioning mode;
  • Step 102 Upload the first positioning data and the original data required by the second positioning mode to the cloud;
  • Step 103 Receive a decision instruction sent by the cloud, where the decision instruction is calculated according to the original data required by the first positioning data and the second positioning mode.
  • the terminal may perform positioning by using the first positioning manner, obtain a positioning result (first positioning data), and acquire original data required by the second positioning mode.
  • first positioning method is used for positioning
  • the original data required for the second positioning mode is obtained, and the two steps may be performed in parallel, or the first positioning method may be used to perform positioning and then acquiring the original required for the second positioning mode.
  • the data or the original data required to obtain the second positioning mode is used to perform the positioning by using the first positioning manner.
  • the order of execution of the two steps is not limited in the embodiment of the present application.
  • the first positioning mode may be a positioning algorithm that is pre-deployed in the terminal, and the second positioning mode may be a positioning algorithm that is pre-deployed in the cloud.
  • the first positioning mode and the second positioning mode may respectively include multiple positioning technologies, and the positioning technologies may be Implemented using existing positioning technology.
  • the terminal sends the original data required by the first positioning result and the second positioning mode to the cloud server, and then waits for the cloud to send the decision instruction, and performs corresponding actions according to the decision instruction, for example, forward, turn, rewind, etc. Wait.
  • the first positioning mode may be deployed in the terminal, and the second positioning mode may be deployed in the cloud, and the terminal sends the positioning data obtained by the first positioning mode and the original data required by the second positioning mode.
  • the cloud can further calculate the location of the terminal, ensuring the accuracy of the positioning while reducing the resource consumption of the terminal.
  • the positioning frequency of the first positioning mode may be higher than the preset first frequency threshold and/or the algorithm complexity is lower than the preset complexity threshold; the positioning frequency of the second positioning mode may be lower than the preset The two frequency thresholds and/or algorithm complexity are higher than the preset complexity threshold.
  • the positioning mode with a higher positioning frequency or a lower algorithm complexity may be deployed on the terminal side, and the positioning mode with a lower positioning frequency or a higher algorithm complexity may be deployed on the cloud side. In this way, the advantages of real-time positioning of the terminal and the high processing power of the cloud can be fully utilized.
  • the first frequency threshold, the second frequency threshold, and the complexity threshold may be preset according to actual needs or experience.
  • the first frequency threshold may be the same as the second frequency threshold, or the first frequency threshold is higher than the second frequency threshold. .
  • the first frequency threshold may be 100 fps
  • the second frequency threshold may be 10 fps.
  • the positioning scheme combining the cloud and the terminal can be selected according to the frequency of the function request. Specifically, high frame rate requirements ( ⁇ 100fps) are deployed locally, medium frame rate requirements ( ⁇ 10fps and ⁇ 100fps) can be deployed on the terminal and the cloud respectively, and low frame rate requirements ( ⁇ 10fps) are deployed on the cloud. .
  • the positioning mode required by the high frame rate may be deployed on the terminal, and the positioning mode required by the low frame rate may be deployed in the cloud.
  • the high frame rate (first frequency threshold) may be 100 fps (the number of frames per second of the picture), and the low frame rate (second frequency threshold) may be 10 fps.
  • the positioning mode requiring the frame rate/positioning frequency ⁇ 100 fps may be deployed locally in the terminal, and the positioning mode of the medium frame rate requirement (ie, ⁇ 10 fps and ⁇ 100 fps) may be separately deployed on the terminal and the cloud. Deploy a low frame rate requirement ( ⁇ 10fps) in the cloud.
  • the first positioning manner may include Global Positioning System (GPS) positioning, wireless positioning, Inertial Measurement Unit (IMU) positioning, and/or visual inertial ranging (VIO, Visual- Inertial Odometry)
  • the first positioning data may include a GPS positioning result, a wireless positioning result, an IMU positioning result, and/or a VIO positioning result.
  • GPS positioning technology combined with GPS technology, wireless communication technology, image processing technology, GIS technology, is currently widely used positioning technology.
  • the wireless positioning technology may include: Bluetooth positioning, RFID positioning, wifi positioning, 4G positioning, etc., and is currently used for indoor positioning.
  • IMU positioning technology is a technique for detecting the attitude of an object by measuring the three-axis attitude angle (angular velocity) and acceleration of the object.
  • the IMU positioning technology can also be classified into IMU step-by-step positioning and IMU depending on whether the object to be positioned is a person or a car.
  • Inertial navigation system INS, inertial navigation system Inertial Navigation System positioning.
  • VIO positioning technology is a combination of camera and inertial measurement unit to estimate position and rotation changes, combining visual and IMU information.
  • the first positioning mode in the embodiment of the present application may include a GPS positioning, a wireless positioning, an IMU positioning, a VIO positioning, and the like, and the positioning technologies may be implemented by using corresponding technical means in the prior art, which is not described herein.
  • the first positioning data may include a GPS positioning result, a wireless positioning result, an IMU positioning result, a VIO positioning result, etc., and any one or several positioning results may be mutually proofed, corrected, output proofread, and corrected positioning. As a result, the present application does not limit this.
  • the original data required by the second positioning mode may be image data
  • the second positioning mode may include Simultaneous localization and mapping (SLAM) positioning.
  • SLAM Simultaneous localization and mapping
  • SLAM positioning technology usually refers to the creation of maps in an unknown environment, while using maps for autonomous positioning and navigation. It can include visual-based SLAM technology vSLAM and lidar-based SLAM technology Lidar SLAM.
  • the original data required by the second positioning mode may be image data, lidar data, or the like.
  • the embodiment of the present application describes a positioning method from the cloud side.
  • FIG. 2 is a schematic flowchart of the implementation of the cloud positioning method in the embodiment of the present application. As shown in the figure, the method may include the following steps:
  • Step 201 Receive first positioning data uploaded by the terminal and original data required by the second positioning mode; the first positioning data is obtained by using the first positioning manner;
  • Step 202 Perform positioning according to the original data required by the second positioning mode by using a second positioning manner to obtain second positioning data.
  • Step 203 Generate a decision instruction according to the first positioning data and the second positioning data, and send the decision instruction to the terminal.
  • the cloud can receive the first positioning data and the original data required by the second positioning mode, and can perform the second positioning mode positioning according to the original data required by the second positioning mode to obtain the positioning result of the second positioning mode positioning (That is, the second positioning data), then merging the first positioning data uploaded by the terminal with the calculated second positioning data, determining the current location of the terminal, and then sending a decision instruction to the terminal to instruct the terminal to move forward, backward, turn, etc. operating.
  • the original data required by the second positioning mode obtained by the receiving terminal is used to perform positioning by using the second positioning mode, and then the positioning result of the second positioning mode is merged with the positioning result obtained by the terminal positioning, thereby To ensure the accuracy of the positioning, in addition, the second positioning mode is deployed in the cloud, which reduces the resource consumption of the terminal to some extent.
  • the positioning frequency of the first positioning mode may be higher than the preset first frequency threshold and/or the algorithm complexity is lower than the preset complexity threshold; the positioning frequency of the second positioning mode may be lower than the preset The two frequency thresholds and/or algorithm complexity are higher than the preset complexity threshold.
  • the positioning mode with a higher positioning frequency or a lower algorithm complexity may be deployed on the terminal side, and the positioning mode with a lower positioning frequency or a higher algorithm complexity may be deployed on the cloud side. In this way, the advantages of real-time positioning of the terminal and the high processing power of the cloud can be fully utilized.
  • the first frequency threshold, the second frequency threshold, and the complexity threshold may be preset according to actual needs or experience.
  • the first frequency threshold may be the same as the second frequency threshold, or the first frequency threshold is higher than the second frequency threshold. .
  • the first frequency threshold may be 100 fps
  • the second frequency threshold may be 10 fps.
  • the positioning mode required by the high frame rate may be deployed on the terminal, and the positioning mode required by the low frame rate may be deployed in the cloud.
  • the high frame rate (first frequency threshold) may be 100 fps (the number of frames per second of the picture), and the low frame rate (second frequency threshold) may be 10 fps.
  • the positioning mode requiring the frame rate/positioning frequency ⁇ 100 fps may be deployed locally in the terminal, and the positioning mode of the medium frame rate requirement (ie, ⁇ 10 fps and ⁇ 100 fps) may be separately deployed on the terminal and the cloud. Deploy a low frame rate requirement ( ⁇ 10fps) in the cloud.
  • the first positioning manner may include GPS positioning, wireless positioning, inertial measurement unit IMU positioning, and/or visual inertial ranging VIO positioning;
  • the first positioning data may include GPS positioning result, wireless positioning result, IMU Position results, and/or VIO positioning results.
  • the first positioning mode in the embodiment of the present application may include a GPS positioning, a wireless positioning, an IMU positioning, a VIO positioning, and the like, and the positioning technologies may be implemented by using corresponding technical means in the prior art, which is not described herein.
  • the first positioning data may include a GPS positioning result, a wireless positioning result, an IMU positioning result, a VIO positioning result, etc., and any one or several positioning results may be mutually proofed, corrected, output proofread, and corrected positioning. As a result, the present application does not limit this.
  • the original data required by the second positioning mode may be image data
  • the second positioning manner may include simultaneous positioning and map creation SLAM positioning.
  • the SLAM positioning technology may include a VSLAM and a Lidar SLAM.
  • the original data required by the second positioning mode may be image data, lidar data, or the like.
  • the embodiment of the present application provides a terminal-side positioning device. Since the principle of solving the problem of these devices is similar to that of the terminal-side positioning method, the repeated description is not repeated, and the following description will be made.
  • FIG. 3 is a schematic structural diagram of a terminal-side positioning device in the embodiment of the present application. As shown in the figure, the positioning device may include:
  • the terminal positioning module 301 is configured to perform positioning by using the first positioning manner to obtain first positioning data.
  • the obtaining module 302 is configured to acquire original data required by the second positioning mode
  • the terminal sending module 303 is configured to upload the first positioning data and the original data required by the second positioning mode to the cloud;
  • the terminal receiving module 304 is configured to receive a decision instruction that is sent by the cloud, where the decision instruction is calculated according to the original data required by the first positioning data and the second positioning mode.
  • the positioning frequency of the first positioning mode is higher than the preset first frequency threshold and/or the algorithm complexity is lower than the preset complexity threshold; the positioning frequency of the second positioning mode is lower than the preset second frequency.
  • the threshold and/or algorithm complexity is higher than the preset complexity threshold.
  • the first frequency threshold is 100 fps and the second frequency threshold is 10 fps.
  • the first positioning manner includes GPS positioning, wireless positioning, inertial measurement unit IMU positioning, and/or visual inertial ranging VIO positioning;
  • the first positioning data includes a GPS positioning result, a wireless positioning result, and an IMU positioning result. , and / or VIO positioning results.
  • the original data required by the second positioning mode is image data
  • the second positioning mode includes simultaneous positioning and map creation SLAM positioning.
  • the embodiment of the present application further provides a cloud side positioning device. Since the principle of solving the problem of these devices is similar to that of the cloud side positioning method, the repeated description is not repeated, and the following description will be made.
  • FIG. 4 is a schematic structural diagram of a cloud side positioning device in the embodiment of the present application. As shown in the figure, the positioning device may include:
  • the cloud receiving module 401 is configured to receive the first positioning data uploaded by the terminal and the original data required by the second positioning mode; the first positioning data is obtained by using the first positioning manner;
  • the cloud positioning module 402 is configured to perform positioning according to the original data required by the second positioning mode by using a second positioning manner to obtain second positioning data.
  • the fusion module 403 is configured to generate a decision instruction according to the first positioning data and the second positioning data;
  • the cloud sending module 404 is configured to send the decision instruction to the terminal.
  • the positioning frequency of the first positioning mode is higher than the preset first frequency threshold and/or the algorithm complexity is lower than the preset complexity threshold; the positioning frequency of the second positioning mode is lower than the preset second frequency.
  • the threshold and/or algorithm complexity is higher than the preset complexity threshold.
  • the first frequency threshold is 100 fps and the second frequency threshold is 10 fps.
  • the first positioning manner includes GPS positioning, wireless positioning, inertial measurement unit IMU positioning, and/or visual inertial ranging VIO positioning;
  • the first positioning data includes a GPS positioning result, a wireless positioning result, and an IMU positioning result. , and / or VIO positioning results.
  • the original data required by the second positioning mode is image data
  • the second positioning mode includes simultaneous positioning and map creation SLAM positioning.
  • An embodiment of the present application provides an electronic device, including: a display, a memory, one or more processors; and one or more modules, the one or more modules are stored in the memory, and configured The execution is performed by the one or more processors, the one or more modules comprising instructions for performing the various steps in the positioning method of the first aspect of the embodiments of the present application.
  • the embodiment of the present application provides a computer program product for encoding an instruction for executing a process, the process comprising the positioning method of the first aspect of the embodiment of the present application.
  • the embodiment of the present application can locate a person, and the person to be located can interact with the cloud by using the terminal device or wearing the wearable device as the terminal.
  • FIG. 5 is a schematic diagram of a pedestrian positioning process according to an embodiment of the present application. As shown in the figure, the embodiment of the present application provides a method for pedestrian behavior based on vision, IMU, and GPS fusion, which is described below.
  • the positioning method combining the cloud and the terminal provided by the embodiment of the present application deploys absolute GPS positioning and relative VIO and IMU step positioning on the terminal, and deploys vSLAM absolute positioning on the cloud, and integrates the positioning combination of the terminal, according to the The resulting decision decision is sent to the terminal.
  • Relative positioning rely on IMU step and VIO positioning to give the result P;
  • a positioning method combining the cloud and the terminal is proposed, and a visual positioning algorithm with low complexity and high frequency is deployed on the terminal to avoid image transmission.
  • the delay causes the stability and accuracy of the visual positioning algorithm to decrease, and deploys a visual relocation method with higher complexity and lower frequency on the cloud to avoid excessive consumption of terminal resources, and integrates absolute positioning and relative positioning to form a An efficient and stable positioning system.
  • the terminal may be an intelligent logistics vehicle robot
  • the cloud may be a server or a server cluster.
  • the interactive positioning process of the intelligent logistics vehicle and the cloud server is described below.
  • FIG. 6 is a schematic diagram showing a process of locating an intelligent logistics vehicle and a cloud server in the embodiment of the present application. As shown in the figure, the positioning process may be as follows:
  • the intelligent logistics vehicle can use the camera to acquire the current scene image, and use the built-in inertial navigation system (or inertial navigation) INS gyroscope and accelerometer to determine the position of the intelligent logistics vehicle; then use the built-in VIO module to perform the current scene image Feature extraction, image processing and other operations combined with odometer and other data to locate intelligent logistics vehicles;
  • the built-in inertial navigation system or inertial navigation
  • the intelligent logistics vehicle can perform the fusion calculation of the two positioning results (inertial navigation positioning and VIO positioning) to obtain the final relative positioning result, and upload the relative positioning result and the current scene image to the cloud server.
  • the intelligent logistics vehicle can also perform GPS positioning according to the built-in GPS module, obtain the GPS absolute positioning result, and upload the GPS absolute positioning result to the cloud server.
  • the cloud server may perform positioning by using the visual SLAM technology according to the current scene image to obtain the absolute positioning result of the vSLAM; and then the absolute positioning result and relative positioning of the GPS uploaded by the terminal. The result is combined with the vSLAM absolute positioning results to obtain the location of the final intelligent logistics vehicle.
  • the cloud server can generate a decision command to send to the intelligent logistics vehicle according to the location of the intelligent logistics vehicle and the destination of the intelligent logistics vehicle, and the intelligent logistics vehicle can perform corresponding operations according to the decision instruction to travel to the destination.
  • the absolute positioning and the relative positioning by integrating the positioning of the intelligent logistics vehicle with the positioning of the cloud server, the absolute positioning and the relative positioning, the stability and accuracy of the positioning are ensured, and the resource consumption of the intelligent logistics vehicle is reduced.
  • embodiments of the present application can be provided as a method, system, or computer program product.
  • the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment in combination of software and hardware.
  • the application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

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Abstract

端云结合定位方法、装置、电子设备及计算机程序产品，包括：终端侧利用第一定位方式定位得到第一定位数据并获取第二定位方式所需的原始数据，将第一定位数据和第二定位方式所需的原始数据上传至云端；云端利用所述原始数据进行第二定位方式定位得到第二定位数据，将所述第一定位数据和第二定位数据进行融合生成决策指令下发至终端。本申请将终端定位与云端定位结合，在降低资源消耗的同时提高了定位准确性。

Description

端云结合定位方法、装置及电子设备、计算机程序产品 技术领域
本申请涉及定位技术，尤其涉及一种端云结合定位方法、装置、电子设备及计算机程序产品。
背景技术
如何实现移动机器人在不确定的环境中自主定位导航，一直是机器人研究的一大核心课题，行业内对这一课题进行了多年的研究。自主定位作为一项核心技术，是赋予机器人感知和行动能力的前提。
目前，智能机器人终端定位处理能力较弱、应用场景非常有限，导致现有的机器人仅能活动在特定的场合，例如：车站、办公室、餐馆和博物馆等等。
作为一种通用的智能机器人，其活动范围应该能够扩展到任意一个场景，因此需要有强大的云端智能算法支持。然而，目前受限于无线传输技术，导致云端的实时处理能力不足。
发明内容
本申请实施例中提供了一种端云结合定位方法、装置、及电子设备、计算机程序产品，可以充分发挥云端和终端各自的优势实现更有效的定位。
根据本申请实施例的第一个方面，提供了一种定位方法，包括如下步骤：
利用第一定位方式进行定位，得到第一定位数据；并获取第二定位方式所需的原始数据；
将所述第一定位数据以及所述第二定位方式所需的原始数据上传至云 端；
接收云端下发的决策指令；所述决策指令为根据所述第一定位数据与第二定位方式所需的原始数据计算得到。
根据本申请实施例的第二个方面，提供了一种定位方法，包括如下步骤：
接收终端上传的第一定位数据以及第二定位方式所需的原始数据；所述第一定位数据为利用第一定位方式定位得到；
根据所述第二定位方式所需的原始数据利用第二定位方式进行定位，得到第二定位数据；
根据所述第一定位数据与所述第二定位数据生成决策指令，并下发至终端。
根据本申请实施例的第三个方面，提供了一种定位装置，包括：
终端定位模块，用于利用第一定位方式进行定位，得到第一定位数据；
获取模块，用于获取第二定位方式所需的原始数据；
终端发送模块，用于将所述第一定位数据以及所述第二定位方式所需的原始数据上传至云端；
终端接收模块，用于接收云端下发的决策指令；所述决策指令为根据所述第一定位数据与第二定位方式所需的原始数据计算得到。
根据本申请实施例的第四个方面，提供了一种定位装置，包括：
云端接收模块，用于接收终端上传的第一定位数据以及第二定位方式所需的原始数据；所述第一定位数据为利用第一定位方式定位得到；
云端定位模块，用于根据所述第二定位方式所需的原始数据利用第二定位方式进行定位，得到第二定位数据；
融合模块，用于根据所述第一定位数据与所述第二定位数据生成决策指令；
云端发送模块，用于将所述决策指令下发至终端。
根据本申请实施例的第五个方面，提供了一种电子设备，该电子设备包括：显示器，存储器，一个或多个处理器；以及一个或多个模块，该一个或多个模块被存储在该存储器中，并被配置成由该一个或多个处理器执行，该一个或多个模块包括用于执行本申请实施例的第一个方面的定位方法中各个步骤的指令。
根据本申请实施例的第六个方面，提供了一种计算机程序产品，该计算机程序产品对用于执行一种过程的指令进行编码，该过程包括本申请实施例的第一个方面的定位方法。
采用根据本申请实施例的定位方法、装置、及电子设备、计算机程序产品，可以将一部分定位方式部署于终端、一部分定位方式部署于云端，充分利用终端的实时处理能力以及云端的计算能力，从而可以确保定位准确性的同时降低终端的资源消耗。
附图说明
此处所说明的附图用来提供对本申请的进一步理解，构成本申请的一部分，本申请的示意性实施例及其说明用于解释本申请，并不构成对本申请的不当限定。在附图中：
图1示出了本申请实施例中终端侧定位方法实施的流程示意图；
图2示出了本申请实施例中云端侧定位方法实施的流程示意图；
图3示出了本申请实施例中终端侧定位装置的结构示意图；
图4示出了本申请实施例中云端侧定位装置的结构示意图；
图5示出了本申请实施例行人定位过程示意图；
图6示出了本申请实施例中智能物流车与云服务器的定位过程示意图。
具体实施方式
以下通过具体示例，进一步阐明本发明实施例技术方案的实质。显然，所描述的实施例仅是本申请的一部分实施例，而不是所有实施例的穷举。需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。
发明人在发明过程中注意到：
目前，定位技术可以分为绝对和相对定位两大类。比如，vSLAM重定位，GPS，WIFI，4G等无线定位技术属于绝对定位。IMU、VIO等定位技术属于相对定位。单独依靠其中任何一种定位技术都不能完全解决机器人的移动问题，所以本申请将这两大类定位方法结合形成——全局用绝对定位，局部用相对定位，并且可以根据算法复杂度和定位频率分别部署在云端和终端，构成一种切实有效的定位系统。
实施例1
本申请实施例从终端侧对定位方法进行说明。
图1示出了本申请实施例中终端侧定位方法实施的流程示意图，如图所示，所述定位方法可以包括如下步骤：
步骤101、利用第一定位方式进行定位，得到第一定位数据；并获取第二定位方式所需的原始数据；
步骤102、将所述第一定位数据以及所述第二定位方式所需的原始数据上传至云端；
步骤103、接收云端下发的决策指令；所述决策指令为根据所述第一定位数据与第二定位方式所需的原始数据计算得到。
具体实施时，终端可以利用第一定位方式进行定位，得到定位结果(第一定位数据)，并且获取到第二定位方式所需的原始数据。其中，利用第一定位方式进行定位，以及获取第二定位方式所需的原始数据，这两个步骤 可以并行执行，也可以先利用第一定位方式进行定位再获取第二定位方式所需的原始数据、或者先获取第二定位方式所需的原始数据再利用第一定位方式进行定位，本申请实施例对这两个步骤的执行顺序不做限定。
第一定位方式可以为预先部署在终端的定位算法，第二定位方式可以为预先部署在云端的定位算法，第一定位方式和第二定位方式分别可以包括多种定位技术，这些定位技术均可以采用现有的定位技术实现。
终端将第一定位结果和第二定位方式所需的原始数据发送给云端服务器，然后就可以等待云端下发决策指令，并根据所述决策指令执行相应的动作，例如：前进、转弯、后退等等。
采用根据本申请实施例的定位方法，可以将第一定位方式部署于终端、第二定位方式部署于云端，终端通过将第一定位方式获得的定位数据以及第二定位方式所需的原始数据发送给云端，从而可以使得云端进一步计算终端的位置，确保定位准确性的同时降低终端的资源消耗。
实施中，所述第一定位方式的定位频率可以高于预设第一频率阈值和/或算法复杂度低于预设复杂度阈值；所述第二定位方式的定位频率可以低于预设第二频率阈值和/或算法复杂度高于预设复杂度阈值。
具体实施时，本申请实施例可以将定位频率较高的、或者算法复杂度较低的定位方式部署于终端侧，而定位频率较低的、或者算法复杂度较高的定位方式部署于云端侧，这样可以充分发挥终端的实时定位优点，以及云端的算法处理能力高的优点。
其中，第一频率阈值、第二频率阈值、复杂度阈值均可以为根据实际需要或经验预先设置，第一频率阈值可以与第二频率阈值相同，或者，第一频率阈值高于第二频率阈值。
实施中，所述第一频率阈值可以为100fps，所述第二频率阈值可以为10fps。
根据工程经验，可以根据功能请求频率的不同选择云端和终端结合的定位方案。具体来说，高帧率要求(≥100fps)部署在本地，中等帧率要求(≥10fps而<100fps)则可以分别部署在终端和云端上，低帧率要求(＜10fps)则部署在云端上。
具体实施时，可以将高帧率要求的定位方式部署在终端，将低帧率要求的定位方式部署在云端。其中，高帧率(第一频率阈值)可以为100fps(画面每秒传输帧数)，低帧率(第二频率阈值)可以为10fps。实际操作时，还可以将要求帧率/定位频率≥100fps的定位方式部署在终端本地，将中等帧率要求(即，≥10fps而<100fps)的定位方式则可以分别部署在终端和云端上，将低帧率要求(＜10fps)的定位方式部署在云端上。
实施中，所述第一定位方式可以包括全球定位系统(GPS，Global Positioning System)定位、无线定位、惯性测量单元(IMU，Inertial Measurement Unit)定位、和/或视觉惯性测距(VIO，Visual-Inertial Odometry)定位；所述第一定位数据可以包括GPS定位结果、无线定位结果、IMU定位结果、和/或VIO定位结果。
GPS定位技术，结合了GPS技术、无线通信技术、图像处理技术、GIS技术，是目前广泛使用的定位技术。
无线定位技术，可以包括：蓝牙定位、RFID定位、wifi定位、4G定位等等，目前常用于室内定位。
IMU定位技术，是通过测量物体三轴姿态角(角速率)以及加速度来检测物体的姿态的技术，IMU定位技术还可以根据待定位物体是人还是车，又可以分为IMU计步定位和IMU惯导定位(INS，惯性导航系统Inertial Navigation System定位)。
VIO定位技术，是将相机和惯性测量单元结合起来估计位置和旋转变化的技术，融合了视觉和IMU的信息。
本申请实施例中第一定位方式可以包括GPS定位、无线定位、IMU定位、VIO定位等等，这些定位技术均可以采用现有技术中相应的技术手段实现，本申请在此不做赘述。
所述第一定位数据可以包括GPS定位结果、无线定位结果、IMU定位结果、VIO定位结果等，也可以将其中任意的一个或几个定位结果进行互相校对、修正，输出校对、修正后的定位结果，本申请对此不作限制。
实施中，所述第二定位方式所需的原始数据可以为图像数据，所述第二定位方式可以包括同时定位与地图创建(SLAM，Simultaneous localization and mapping)定位。
SLAM定位技术，通常是指在未知环境中创建地图、同时利用地图进行自主定位和导航，可以包括基于视觉的SLAM技术vSLAM和基于激光雷达的SLAM技术Lidar SLAM等。
所述第二定位方式为SLAM定位技术时，所述第二定位方式所需的原始数据可以为图像数据、激光雷达数据等等。
实施例2
本申请实施例从云端侧对定位方法进行说明。
图2示出了本申请实施例中云端定位方法实施的流程示意图，如图所示，所述方法可以包括如下步骤：
步骤201、接收终端上传的第一定位数据以及第二定位方式所需的原始数据；所述第一定位数据为利用第一定位方式定位得到；
步骤202、根据所述第二定位方式所需的原始数据利用第二定位方式进行定位，得到第二定位数据；
步骤203、根据所述第一定位数据与所述第二定位数据生成决策指令，并下发至终端。
云端可以接收终端上传的第一定位数据和第二定位方式所需的原始数 据，可以首先根据第二定位方式所需的原始数据进行第二定位方式定位，得到第二定位方式定位的定位结果(即第二定位数据)，然后将终端上传的第一定位数据与计算得到的第二定位数据进行融合，确定终端的当前位置，然后向终端发送决策指令，指示终端进行前进、后退、转弯等移动操作。
本申请实施例中，云端通过接收终端采集获得的第二定位方式所需的原始数据利用第二定位方式进行定位，然后将第二定位方式的定位结果与终端定位得到的定位结果进行融合，从而确保定位的准确性，此外，将第二定位方式部署在云端，在一定程度上降低了终端的资源消耗。
实施中，所述第一定位方式的定位频率可以高于预设第一频率阈值和/或算法复杂度低于预设复杂度阈值；所述第二定位方式的定位频率可以低于预设第二频率阈值和/或算法复杂度高于预设复杂度阈值。
具体实施时，本申请实施例可以将定位频率较高的、或者算法复杂度较低的定位方式部署于终端侧，而定位频率较低的、或者算法复杂度较高的定位方式部署于云端侧，这样可以充分发挥终端的实时定位优点，以及云端的算法处理能力高的优点。
其中，第一频率阈值、第二频率阈值、复杂度阈值均可以为根据实际需要或经验预先设置，第一频率阈值可以与第二频率阈值相同，或者，第一频率阈值高于第二频率阈值。
实施中，所述第一频率阈值可以为100fps，所述第二频率阈值可以为10fps。
具体实施时，可以将高帧率要求的定位方式部署在终端，将低帧率要求的定位方式部署在云端。其中，高帧率(第一频率阈值)可以为100fps(画面每秒传输帧数)，低帧率(第二频率阈值)可以为10fps。实际操作时，还可以将要求帧率/定位频率≥100fps的定位方式部署在终端本地，将中等帧率要求(即，≥10fps而<100fps)的定位方式则可以分别部署在终 端和云端上，将低帧率要求(＜10fps)的定位方式部署在云端上。
实施中，所述第一定位方式可以包括GPS定位、无线定位、惯性测量单元IMU定位、和/或视觉惯性测距VIO定位；所述第一定位数据可以包括GPS定位结果、无线定位结果、IMU定位结果、和/或VIO定位结果。
本申请实施例中第一定位方式可以包括GPS定位、无线定位、IMU定位、VIO定位等等，这些定位技术均可以采用现有技术中相应的技术手段实现，本申请在此不做赘述。
所述第一定位数据可以包括GPS定位结果、无线定位结果、IMU定位结果、VIO定位结果等，也可以将其中任意的一个或几个定位结果进行互相校对、修正，输出校对、修正后的定位结果，本申请对此不作限制。
实施中，所述第二定位方式所需的原始数据可以为图像数据，所述第二定位方式可以包括同时定位与地图创建SLAM定位。
SLAM定位技术可以包括vSLAM和Lidar SLAM等，所述第二定位方式为SLAM定位技术时，所述第二定位方式所需的原始数据可以为图像数据、激光雷达数据等等。
实施例3
基于同一发明构思，本申请实施例提供了一种终端侧定位装置，由于这些设备解决问题的原理与一种终端侧定位方法相似，故重复之处不再赘述，下面进行说明。
图3示出了本申请实施例中终端侧定位装置的结构示意图，如图所示，所述定位装置可以包括：
终端定位模块301，用于利用第一定位方式进行定位，得到第一定位数据；
获取模块302，用于获取第二定位方式所需的原始数据；
终端发送模块303，用于将所述第一定位数据以及所述第二定位方式所 需的原始数据上传至云端；
终端接收模块304，用于接收云端下发的决策指令；所述决策指令为根据所述第一定位数据与第二定位方式所需的原始数据计算得到。
实施中，所述第一定位方式的定位频率高于预设第一频率阈值和/或算法复杂度低于预设复杂度阈值；所述第二定位方式的定位频率低于预设第二频率阈值和/或算法复杂度高于预设复杂度阈值。
实施中，所述第一频率阈值为100fps，所述第二频率阈值为10fps。
实施中，所述第一定位方式包括GPS定位、无线定位、惯性测量单元IMU定位、和/或视觉惯性测距VIO定位；所述第一定位数据包括GPS定位结果、无线定位结果、IMU定位结果、和/或VIO定位结果。
实施中，所述第二定位方式所需的原始数据为图像数据，所述第二定位方式包括同时定位与地图创建SLAM定位。
实施例4
基于同一发明构思，本申请实施例还提供了一种云端侧定位装置，由于这些设备解决问题的原理与一种云端侧定位方法相似，故重复之处不再赘述，下面进行说明。
图4示出了本申请实施例中云端侧定位装置的结构示意图，如图所示，所述定位装置可以包括：
云端接收模块401，用于接收终端上传的第一定位数据以及第二定位方式所需的原始数据；所述第一定位数据为利用第一定位方式定位得到；
云端定位模块402，用于根据所述第二定位方式所需的原始数据利用第二定位方式进行定位，得到第二定位数据；
融合模块403，用于根据所述第一定位数据与所述第二定位数据生成决策指令；
云端发送模块404，用于将所述决策指令下发至终端。
实施中，所述第一定位方式的定位频率高于预设第一频率阈值和/或算法复杂度低于预设复杂度阈值；所述第二定位方式的定位频率低于预设第二频率阈值和/或算法复杂度高于预设复杂度阈值。
实施中，所述第一频率阈值为100fps，所述第二频率阈值为10fps。
实施中，所述第一定位方式包括GPS定位、无线定位、惯性测量单元IMU定位、和/或视觉惯性测距VIO定位；所述第一定位数据包括GPS定位结果、无线定位结果、IMU定位结果、和/或VIO定位结果。
实施中，所述第二定位方式所需的原始数据为图像数据，所述第二定位方式包括同时定位与地图创建SLAM定位。
实施例5
本申请实施例提供了一种电子设备，该电子设备包括：显示器，存储器，一个或多个处理器；以及一个或多个模块，该一个或多个模块被存储在该存储器中，并被配置成由该一个或多个处理器执行，该一个或多个模块包括用于执行本申请实施例的第一个方面的定位方法中各个步骤的指令。
实施例6
本申请实施例提供了一种计算机程序产品，该计算机程序产品对用于执行一种过程的指令进行编码，该过程包括本申请实施例的第一个方面的定位方法。
实施例7
为了便于实施，本申请实施例以一实例进行说明。
本申请实施例可以对人进行定位，待定位的人可以手持终端设备或者佩戴可穿戴设备作为终端与云端交互。
图5示出了本申请实施例行人定位过程示意图，如图所示，本申请实施例提供了一种端云结合的基于视觉、IMU、GPS融合的行人行为方法，下面进行说明。
本申请实施例所提供的云端和终端结合的定位方法，在终端上部署绝对GPS定位和相对VIO、IMU计步定位，在云端上部署了vSLAM绝对定位，并且融合了终端的定位结合，根据该结果形成决策指令发送至终端。
具体过程可以如下：
1、在终端侧，采集相机、IMU和GPS的原始数据以及时间戳；
2、在终端侧，绝对定位：依靠GPS的定位给出结果GPS；
            相对定位：依靠IMU计步和VIO定位给出结果P；
3、在终端侧，将图像、结果GPS和P发送到云端；
4、在云端侧，绝对定位：将图像输入vSLAM给出视觉重定位结果；
5、在云端侧，融合vSLAM和GPS的绝对定位结果以及相对定位结果P，给出当前的位置；
6、在云端侧，根据当前的位置，给出决策并发送至终端。
本申请实施例根据定位算法复杂度大小、定位功能请求频率的高低，提出了一种云端和终端结合的定位方法，在终端上部署复杂度较低、频率较高的视觉定位算法，避免图像传输的延迟造成视觉定位算法的稳定性和准确性下降，在云端上部署复杂度较高、频率较低的视觉重定位方法，避免过多消耗终端的资源，将绝对定位和相对定位融合，形成一种高效和稳定的定位系统。
实施例8
为了便于本申请的理解，本申请实施例以另一实例进行说明。
本申请实施例中终端可以为智能物流车机器人，云端可以为服务器或服务器集群，下面对智能物流车和云服务器的交互定位过程进行说明。
图6示出了本申请实施例中智能物流车与云服务器的定位过程示意图，如图所示，定位过程可以如下：
智能物流车可以利用摄像头获取当前场景图像，并且利用内置的惯性导航系统(或简称惯导)INS的陀螺仪和加速度计来测定智能物流车的位置；然后利用内置的VIO模块对当前场景图像进行特征提取、图像处理等操作并结合里程计等数据对智能物流车进行定位；
智能物流车可以将两次定位的结果(惯导定位以及VIO定位)进行融合计算，得到最终的相对定位结果，并将相对定位结果和当前场景图像上传至云服务器。
此外，智能物流车还可以根据内置的GPS模块进行GPS定位，得到GPS绝对定位结果，并将GPS绝对定位结果同样上传至云服务器。
云服务器获取到当前场景图像以及终端上传的相对定位结果、绝对定位结果之后，可以根据当前场景图像利用视觉SLAM技术进行定位，得到vSLAM绝对定位结果；然后将终端上传的GPS绝对定位结果、相对定位结果与vSLAM绝对定位结果进行融合，得到最终的智能物流车的位置。
最后，云服务器根据智能物流车的位置、以及智能物流车的目的地等信息，可以生成决策指令发送给智能物流车，智能物流车可以根据决策指令进行相应的操作以向目的地行进。
本申请实施例通过将智能物流车的定位与云服务器的定位融合、绝对定位与相对定位融合，实现了确保定位稳定性和准确性的同时降低智能物流车的资源消耗。
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不 限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本申请的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本申请范围的所有变更和修改。
显然，本领域的技术人员可以对本申请进行各种改动和变型而不脱离本申请的精神和范围。这样，倘若本申请的这些修改和变型属于本申请权 利要求及其等同技术的范围之内，则本申请也意图包含这些改动和变型在内。

Claims (14)

  1. 一种定位方法，其特征在于，包括如下步骤：
    利用第一定位方式进行定位，得到第一定位数据；并获取第二定位方式所需的原始数据；
    将所述第一定位数据以及所述第二定位方式所需的原始数据上传至云端；
    接收云端下发的决策指令；所述决策指令为根据所述第一定位数据与第二定位方式所需的原始数据计算得到。
  2. 一种定位方法，其特征在于，包括如下步骤：
    接收终端上传的第一定位数据以及第二定位方式所需的原始数据；所述第一定位数据为利用第一定位方式定位得到；
    根据所述第二定位方式所需的原始数据利用第二定位方式进行定位，得到第二定位数据；
    根据所述第一定位数据与所述第二定位数据生成决策指令，并下发至终端。
  3. 如权利要求1或2所述的方法，其特征在于，所述第一定位方式的定位频率高于预设第一频率阈值和/或算法复杂度低于预设复杂度阈值；所述第二定位方式的定位频率低于预设第二频率阈值和/或算法复杂度高于预设复杂度阈值。
  4. 如权利要求3所述的方法，其特征在于，所述第一频率阈值为100fps，所述第二频率阈值为10fps。
  5. 如权利要求1或2所述的方法，其特征在于，所述第一定位方式包括GPS定位、无线定位、惯性测量单元IMU定位、和/或视觉惯性测距VIO定位；所述第一定位数据包括GPS定位结果、无线定位结果、IMU定位结果、和/或VIO定位结果。
  6. 如权利要求1或2所述的方法，其特征在于，所述第二定位方式所需的原始数据为图像数据，所述第二定位方式包括同时定位与地图创建SLAM定位。
  7. 一种定位装置，其特征在于，包括：
    终端定位模块，用于利用第一定位方式进行定位，得到第一定位数据；
    获取模块，用于获取第二定位方式所需的原始数据；
    终端发送模块，用于将所述第一定位数据以及所述第二定位方式所需的原始数据上传至云端；
    终端接收模块，用于接收云端下发的决策指令；所述决策指令为根据所述第一定位数据与第二定位方式所需的原始数据计算得到。
  8. 一种定位装置，其特征在于，包括：
    云端接收模块，用于接收终端上传的第一定位数据以及第二定位方式所需的原始数据；所述第一定位数据为利用第一定位方式定位得到；
    云端定位模块，用于根据所述第二定位方式所需的原始数据利用第二定位方式进行定位，得到第二定位数据；
    融合模块，用于根据所述第一定位数据与所述第二定位数据生成决策指令；
    云端发送模块，用于将所述决策指令下发至终端。
  9. 如权利要求7或8所述的装置，其特征在于，所述第一定位方式的定位频率高于预设第一频率阈值和/或算法复杂度低于预设复杂度阈值；所述第二定位方式的定位频率低于预设第二频率阈值和/或算法复杂度高于预设复杂度阈值。
  10. 如权利要求9所述的装置，其特征在于，所述第一频率阈值为100fps，所述第二频率阈值为10fps。
  11. 如权利要求7或8所述的装置，其特征在于，所述第一定位方式 包括GPS定位、无线定位、惯性测量单元IMU定位、和/或视觉惯性测距VIO定位；所述第一定位数据包括GPS定位结果、无线定位结果、IMU定位结果、和/或VIO定位结果。
  12. 如权利要求7或8所述的装置，其特征在于，所述第二定位方式所需的原始数据为图像数据，所述第二定位方式包括同时定位与地图创建SLAM定位。
  13. 一种电子设备，其特征在于，所述电子设备包括：显示器，存储器，一个或多个处理器；以及一个或多个模块，所述一个或多个模块被存储在所述存储器中，并被配置成由所述一个或多个处理器执行，所述一个或多个模块包括用于执行权利要求1-6中任一所述方法中各个步骤的指令。
  14. 一种计算机程序产品，所述计算机程序产品对用于执行一种过程的指令进行编码，所述过程包括根据权利要求1-6中任一项所述的方法。
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