WO2020082947A1 - 行进控制的方法、设备及存储介质 - Google Patents

行进控制的方法、设备及存储介质 Download PDF

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Publication number
WO2020082947A1
WO2020082947A1 PCT/CN2019/106967 CN2019106967W WO2020082947A1 WO 2020082947 A1 WO2020082947 A1 WO 2020082947A1 CN 2019106967 W CN2019106967 W CN 2019106967W WO 2020082947 A1 WO2020082947 A1 WO 2020082947A1
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WIPO (PCT)
Prior art keywords
area
mobile device
obstacle
self
height
Prior art date
Application number
PCT/CN2019/106967
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English (en)
French (fr)
Inventor
李毅兰
谢凯旋
Original Assignee
科沃斯机器人股份有限公司
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.)
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Publication date
Application filed by 科沃斯机器人股份有限公司 filed Critical 科沃斯机器人股份有限公司
Priority to EP19876513.3A priority Critical patent/EP3872528A4/en
Publication of WO2020082947A1 publication Critical patent/WO2020082947A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
    • G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/24—Floor-sweeping machines, motor-driven
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A47L11/4011—Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
    • A47L2201/04—Automatic control of the travelling movement; Automatic obstacle detection

Definitions

  • This application relates to the field of artificial intelligence technology, and in particular to a method, device and storage medium for travel control.
  • the sweeping robot In the process of sweeping the ground, the sweeping robot needs to avoid obstacles in order to better perform the cleaning work.
  • the obstacle avoidance function of the sweeping robot is generally realized by the cooperation of infrared, laser, ultrasonic and other distance sensors and spring baffles. After the distance sensor detects that there is an obstacle in front or the spring baffle touches the obstacle, the machine will return according to the obstacle avoidance control instructions Or bypass.
  • Various aspects of the present application provide a method for traveling control of a mobile device, which solves the problem of inaccurate judgment of obstacles by a mobile device in the prior art, and improves the obstacle avoidance capability of the mobile device.
  • the embodiments of the present application provide a method for traveling control, which is suitable for mobile devices and includes:
  • Three-dimensional environment information collected from the traveling path of the mobile device
  • the traveling control of the mobile device is performed for the obstacle area.
  • An embodiment of the present application further provides a self-moving device, including: a mechanical body provided with an area array solid-state laser radar, one or more processors, and one or more memories storing computer programs;
  • the area array solid-state laser radar is used to collect three-dimensional environmental information on the traveling path of the mobile device
  • the one or more processors are used to execute the computer program for:
  • the traveling control of the mobile device is performed for the obstacle area.
  • An embodiment of the present application further provides a computer-readable storage medium storing a computer program, and when the computer program is executed by one or more processors, causing the one or more processors to perform actions including the following:
  • Three-dimensional environment information collected from the traveling path of the mobile device
  • the traveling control of the mobile device is performed for the obstacle area.
  • the self-mobile device collects three-dimensional environment information on its own travel path during travel, and based on the three-dimensional environment information, identifies the obstacle areas and types present on the travel path of the self-mobile device. For different area types, different travel control is adopted in a targeted manner, and the travel control method of this application is adopted to improve the obstacle avoidance performance of the mobile device.
  • FIG. 1 is a method flowchart of a travel control method provided by an exemplary embodiment of the present application
  • FIG. 2 is a schematic diagram of the presence of a threshold stone in front of a cleaning robot according to an exemplary embodiment of the present application
  • FIG. 3 is a schematic diagram of an upper step in front of the cleaning robot according to an exemplary embodiment of the present application
  • FIG. 4 is a schematic diagram of an upward slope in front of the cleaning robot according to an exemplary embodiment of the present application.
  • FIG. 5 is a schematic diagram of an exemplary embodiment of the present application forming a gap that restricts the height of the cleaning robot
  • FIG. 6 is a schematic diagram of a gap forming a constraint on the width of the cleaning robot according to an exemplary embodiment of the present application
  • FIG. 7 is a schematic diagram of the presence of a lower step in front of the cleaning robot according to an exemplary embodiment of the present application.
  • FIG. 8 is a schematic diagram of a downward slope in front of the cleaning robot according to an exemplary embodiment of the present application.
  • FIG. 9 is a structural block diagram of a mobile device provided by an exemplary embodiment of the present application.
  • FIG. 10 is a structural block diagram of a robot provided by an exemplary embodiment of the present application.
  • LDS technology In the practical application of home robots, it is necessary to measure and map the obstacle information in the scene, so as to carry out effective obstacle avoidance and path planning.
  • Vslam technology In the case of incomplete drawings, when encountering unknown obstacles, the machine needs to perform dynamic obstacle avoidance. LDS can only detect obstacle information in a plane, and the vertical direction cannot be measured, which is easy to cause the fuselage to often drill into narrow gaps. The cabinet bottom, bed bottom and other areas are stuck and cause unnecessary movements. The lack of landmark information in the data obtained by Vslam causes the robot to judge the obstacles inaccurately.
  • the self-mobile device collects three-dimensional environmental information on its own travel path during the travel process, and recognizes the self-movement based on the three-dimensional environmental information Obstacle areas and their types on the traveling path of the device, since the mobile device adopts different traveling controls for different types of areas, and adopts the traveling control method of the present application to improve the obstacle avoidance performance of the mobile device.
  • FIG. 1 is a method flowchart of a method for traveling control provided by an exemplary embodiment of the present application. As shown in FIG. 1, the method includes:
  • S101 Three-dimensional environment information collected from the traveling path of the mobile device
  • S102 Based on the three-dimensional environment information, identify the obstacle area and its type existing on the travel path of the mobile device;
  • the execution body of the above method in the embodiments of the present application may be self-mobile devices, such as unmanned vehicles and robots, and the types of robots and unmanned vehicles are not limited.
  • the robots may be sweeping robots, following robots, and welcome robots.
  • Different devices can obtain the 3D environment information in the corresponding working environment for different working environments. For example, during the cleaning process of the household, the sweeping robot can obtain the 3D environment images of the living room, kitchen, toilet, horizontal and other areas during the travel process. ;
  • Shopping mall shopping guide robots can obtain three-dimensional environmental images of pedestrian passages, shops and other areas during the shopping process of customers; during the process of following the target, the following robot can obtain the following target and progress Three-dimensional environmental information of the surrounding environment in the process.
  • the three-dimensional environment information on the travel path of the self-mobile device is collected in real time.
  • area array solid-state laser radar can quickly and accurately obtain a large amount of three-dimensional information, which satisfies the information requirement in the process of positioning and mapping.
  • the area array solid-state lidar uses a diffraction beam splitting element to perform n * n beam splitting on the emitted laser beam.
  • a single beam splitter uses the principle of triangulation ranging, that is, the emitted laser beam is collimated by the beam expander to illuminate the target surface, and the target echo received by the system is received.
  • the position of the center of the scattered light spot is measured by the position-sensitive original price, and the multi-beam spectral information is fused to obtain three-dimensional data information.
  • the three-dimensional environment information collected on the traveling path of the mobile device is collected based on the area array lidar to identify the obstacle area and the type existing on the traveling path of the mobile device.
  • an abnormal area on the travel path of the mobile device is identified as an obstacle area; the type of the obstacle area is determined according to the abnormal state of the obstacle area relative to the work plane. This embodiment determines the obstacle area and the type of the obstacle area at a certain distance from the obstacle, and performs different travel control on the self-mobile device for different types of obstacle areas.
  • the types of the obstacle area may include the following three types: the area to be overturned, the area to jump down, and the area to be crossed. The following explains how to determine the type of each obstacle area based on the abnormal state of the obstacle area relative to the working plane.
  • a threshold stone (FIG. 2 is a schematic diagram of a threshold stone in front of the cleaning robot according to an exemplary embodiment of the present application, and the direction indicated by the arrow is the movement of the cleaning robot Direction), upper steps (FIG. 3 is a schematic diagram of the presence of upper steps in front of the sweeping robot of the exemplary embodiment of the present application, and the direction indicated by the arrow is the traveling direction of the sweeping robot) and upward slope (FIG. 4 is the sweeping robot of the exemplary embodiment of the present application There is a schematic diagram of an upward slope ahead, and the direction indicated by the arrow is the traveling direction of the cleaning robot).
  • FIG. 7 is a schematic diagram of the existence of a lower step in front of the cleaning robot according to an exemplary embodiment of the present application.
  • the direction refers to the traveling direction of the cleaning robot
  • FIG. 8 is a schematic diagram of the downward slope in front of the cleaning robot according to the exemplary embodiment of the present application, and the direction indicated by the arrow is the traveling direction of the cleaning robot), etc.
  • the gap that restricts the width or length of the self-moving device includes the narrow corridor gap ( Figure 6 is an exemplary implementation of this application
  • the width of the cleaning robot is constrained by the gap), for example: the gap formed between various types of furniture (between the sofa and the coffee table, between the bed and the cabinet, between the table and the chair, etc.), the gap formed by the furniture itself (chair Legs, between table legs, etc.).
  • the self-mobile device After identifying the obstacle area and the type of the obstacle area existing on the self-moving traveling path, according to the type of the obstacle area and combining the relative size relationship between the self-mobile device and the obstacle area, the self-mobile device is controlled for the movement of the obstacle area.
  • the following describes the corresponding travel control method for the mobile device for different types of obstacle areas.
  • the height of the obstacle in the area to be overturned is calculated; according to the relationship between the height of the obstacle and the first threshold, the traveling control of the self-mobile device is performed for the area to be overturned.
  • the mobile device is controlled to perform the obstacle avoidance operation; if the height of the obstacle is less than the first threshold, the mobile device is controlled to roll over the area to be overturned.
  • the first threshold value is less than or equal to the height of the body of the mobile device from the work plane.
  • the obstacle avoidance operation performed by the mobile device can be the mobile device walking around the obstacle.
  • the relationship between the height of the slope and the first threshold can be used to control the travel of the mobile device for the area to be overturned.
  • the relationship between the inclination angle of the inclined plane and the third threshold may also be used to control the travel of the self-mobile device for the area to be overturned.
  • the self-mobile device may be controlled for the area to be overturned.
  • the self-mobile device When the self-mobile device needs to cross the area to be overturned, in order to improve the success rate of the self-mobile device to overturn the obstacle, it is necessary to control the self-mobile device to speed up to overturn the area to be overturned.
  • the first speed is the product of the height of the obstacle, the travel speed preset from the mobile device, and the preset first rate coefficient.
  • the first speed V1 h * a1 * v, where h is the height of the obstacle; a1 is the rate coefficient measured according to the experiment; and v is the forward speed when the mobile device is working normally.
  • the advancing speed of the self-mobile device is adjusted according to the height of the obstacle, and the self-mobile device accelerates over the obstacle to increase the smoothness of the overturn.
  • the speed of the mobile device over the obstacle can also be calculated using other methods, and the mobile device can also overstep the obstacle at the original speed.
  • the depth of the sinking space in the area to be lowered is calculated; according to the relationship between the depth of the sinking space and the second threshold, the self-mobile device is controlled for the area to be lowered .
  • the second threshold is less than or equal to the height from the body of the mobile device to the working plane.
  • the traveling control of the self-mobile device can be performed for the area to be lowered.
  • the current party is a sinking space that is much larger than the mobile device
  • calculate The relationship between the depth of the sinking space and the second threshold determines that the mobile device performs the obstacle avoidance operation or jumps to the sinking space to continue working.
  • the obstacle avoidance operation performed by the self-mobile device can walk around the sinking space for the self-mobile device.
  • the relationship between the height of the slope and the second threshold may be used to control the travel of the mobile device for the area to be overturned.
  • the relationship between the inclination angle of the inclined plane and the fourth threshold may also be used to control the travel of the self-mobile device for the area to be overturned.
  • the self-mobile device may be controlled for the area to be overturned.
  • the self-mobile device When the self-mobile device needs to jump to the area to be lowered, in order to improve the stability of the jump from the mobile device to the area to be lowered, it is necessary to control the self-mobile device to decrease the speed to jump to the area to be lowered.
  • the second speed from the mobile device to the area to be lowered is calculated; from the mobile device to the second speed to the area to be lowered along the travel path .
  • the second speed is the product of the inverse of the depth of the sinking space, the travel speed preset from the mobile device, and the preset second rate coefficient.
  • the second speed V2 (1 / d) * a2 * v, where d is the depth of the sinking space, a2 is the rate coefficient measured according to the experiment, and v is the advancing speed from the normal operation of the mobile device.
  • the advancing speed of the mobile device is adaptively adjusted according to the depth of the sinking space, and the mobile device decelerates and jumps to the sinking space to continue working, thereby increasing the smoothness of the movement of the mobile device.
  • the speed from the mobile device to the sinking space can also be calculated by other methods, and the mobile device can also jump to the sinking space at the original speed.
  • the height and width of the gap in the area to be traversed are calculated; according to the relationship between the height and width of the gap and the height of the body of the self-mobile device, the self-mobile device travels for the area to be traversed control.
  • the mobile device is controlled to continue to travel through the area to be traversed according to the travel path; If at least one of the conditions that the width is less than or equal to the width of the body of the mobile device and the height of the gap is less than or equal to the height of the body of the mobile device is satisfied, the obstacle avoidance operation is performed. That is, if the space of the gap is sufficient to allow the self-mobile device to pass, the self-mobile device passes through the gap, otherwise, the self-mobile device is controlled to perform the obstacle avoidance operation.
  • the self-mobile device can be controlled to speed up crossing the area to be traversed.
  • the preset travel speed of the self-mobile device and the width of the gap calculate the third speed of the self-mobile device to continue to travel through the area to be traversed according to the travel path; the self-mobile device to continue to travel through the to-be-traversed path at the third speed region.
  • the third speed is the product of the width of the gap, the travel speed preset from the mobile device, and the preset third rate coefficient.
  • the third speed V3 b * a3 * v, where b is the width or height of the gap, a3 is the rate coefficient measured according to experiments, and v is the forward speed when the mobile device is working normally.
  • the embodiment of the present application adaptively adjusts the advancing speed of the self-mobile device according to the height and width information of the gap, the self-mobile device accelerates through the gap, and increases the smoothness of the movement of the self-mobile device.
  • the speed of traversing the gap from the mobile device can also be calculated in other ways, and the speed of the mobile device can also traverse the gap at the original speed.
  • Application scenario 1 In the driving scenario of an unmanned vehicle, the unmanned vehicle uses the area array solid-state lidar installed on the body of the unmanned vehicle to collect the road surface information on the traveling path in real time. When there are trees lying down on the road surface on the path of the unmanned vehicle, the unmanned vehicle obtains the three-dimensional information of the trees on the road surface through the area array solid-state laser radar, and the abnormal state on the road surface is obtained through analysis to determine the road surface
  • the area in front is an obstacle area, and there are obstacles protruding from the road surface in the obstacle area. Determine the obstacle area as the area to be overturned.
  • Application Scenario 2 In the scenario of a sweeping robot cleaning the ground, the sweeping robot uses the area array solid-state lidar installed in front of the machine body to collect real-time ground information on the travel path to obtain three-dimensional information on the ground. When there is a chair on the path, the sweeping robot obtains the three-dimensional information of the chair on the road in front by the area array solid-state laser radar, and the abnormal state on the ground in front of the ground is analyzed, and the area in front of the ground is determined to be an obstacle area.
  • Gap determine the obstacle area as the area to be traversed, calculate the height and width of the gap under the chair, if the width of the gap under the chair is greater than the width of the sweeping robot, and the height of the gap under the chair is greater than the sweeping robot installation, control the sweeping robot to continue along the path of travel Continue to clean under the chair, if the width of the gap under the chair is less than or equal to the width of the cleaning robot, and the height of the gap is less than or equal to the total height of the cleaning robot, the sweeping machine People continue to bypass the chair cleaning work.
  • the sweeping robot needs to cross the gap under the chair.
  • the sweeping robot can be controlled to speed up Speed through the gap under the chair.
  • the speed of the cleaning robot passing through the gap under the chair is the product of the width of the gap, the preset travel speed of the cleaning robot and the preset rate coefficient.
  • Application scenario 3 In the shopping guide scenario of shopping mall shopping guide robots, shopping mall shopping robots use area array solid-state lidar installed on the machine body to collect real-time ground information on the travel path to obtain three-dimensional information on the ground, when shopping mall shopping guide When there is a lower step on the traveling path in front of the robot, the shopping guide robot obtains the three-dimensional information of the lower step on the road surface through the area array solid-state lidar. After analysis, it is found that there is an abnormal state on the ground in front, and the area in front of the ground is determined as an obstacle area.
  • the shopping guide robot There is a sinking space below the ground in the obstacle area, determine the obstacle area as the area to be lowered, calculate the depth of the sinking space, if the depth of the sinking space is greater than or equal to the height of the body of the shopping guide robot, the shopping guide robot will detour; If the depth of the sinking space is less than the height of the body of the shopping guide robot, the shopping guide robot jumps down to the ground below the steps and continues to work.
  • the shopping guide robot needs to jump down to the area to be lowered, in order to improve the stability of the shopping guide robot jumping down to the sinking space under the step, the shopping guide robot needs to be controlled to reduce the speed to jump down to the sinking space under the step.
  • the speed of the shopping guide robot jumping down to the sinking space below the steps is the product of the reciprocal of the depth of the sinking space, the preset travel speed of the shopping guide robot and the preset rate coefficient.
  • the self-moving device includes one or more processors 902 and one or more memories 903 and sensors 905 storing computer programs.
  • the sensor 905 is an area solid-state lidar 905, which is used to collect three-dimensional environmental information on the traveling path of the mobile device; it may also include necessary components such as an audio component 901 and a power component 904.
  • One or more processors 902 are used to execute computer programs for:
  • Three-dimensional environment information collected from the traveling path of the mobile device
  • the traveling control of the mobile device is performed for the obstacle area.
  • one or more processors 902 based on the three-dimensional environment information, identify the obstacle area and the type present on the travel path of the mobile device, and are used to: based on the three-dimensional environment information, identify the abnormal area on the travel path of the mobile device As an obstacle area; according to the abnormal state of the obstacle area relative to the working plane, determine the type of the obstacle area.
  • one or more processors 902 determine the type of the obstacle area according to the abnormal state of the obstacle area relative to the work plane, and are used to: if there is an obstacle protruding from the work plane in the obstacle area, determine the obstacle area as a pending Overturn the area; if there is a sinking space below the working plane in the obstacle area, determine the obstacle area as the area to be lowered; if there is a gap in the obstacle area at the same height as the work plane, determine the obstacle area as the area to be traversed.
  • one or more processors 902 based on the type of the obstacle area, control the travel of the self-mobile device for the obstacle area, and are used to: according to the type of the obstacle area, combine the relative size relationship between the self-mobile device and the obstacle area, Control the travel of the mobile device for the obstacle area.
  • one or more processors 902 perform travel control on the self-mobile device for the obstacle area, and are used to: if the type of the obstacle area is Calculate the height of the obstacle in the area to be overturned according to the relationship between the height of the obstacle and the first threshold, and control the travel of the self-mobile device for the area to be overturned, where the first threshold is less than or equal to the The height of the fuselage from the working plane.
  • the one or more processors 902 perform travel control on the self-mobile device for the area to be overturned, if: the height of the obstacle is greater than or If it is equal to the first threshold, the mobile device is controlled to perform the obstacle avoidance operation; if the height of the obstacle is less than the first threshold, the mobile device is controlled to roll over the area to be overturned.
  • one or more processors 902 perform travel control on the self-mobile device for the obstacle area, and are used to: if the type of the obstacle area is Calculate the depth of the sinking space in the area to be lowered; based on the relationship between the depth of the sinking space and the second threshold, perform travel control on the mobile device for the area to be lowered, where the second threshold is less than It is equal to the height of the mobile device from the working plane.
  • the one or more processors 902 perform travel control on the self-mobile device for the area to be lowered, for: if the depth of the sinking space is greater than or equal to the second Threshold value, the obstacle avoidance operation is performed; if the depth of the sinking space is less than the second threshold value, the control jumps from the mobile device to the area to be jumped to continue working.
  • one or more processors 902 perform travel control on the self-mobile device for the obstacle area, and are used to: if the type of the obstacle area is For the area to be traversed, calculate the height and width of the gap in the area to be traversed; according to the relationship between the height and width of the gap and the height of the body of the self-mobile device, the travel control of the self-mobile device is performed for the area to be traversed.
  • the one or more processors 902 perform travel control on the mobile device for the area to be traversed, and are used to: The width of the body of the mobile device, and the height of the gap is greater than the height of the body of the mobile device, then the self-mobile device is controlled to continue to travel through the area to be traversed according to the travel path; if the width of the gap is less than or equal to the width of the body of the mobile device If the height of the gap is less than or equal to the height of the body of the mobile device, at least one of the conditions is met, then the obstacle avoidance operation is performed.
  • the self-mobile device collects the three-dimensional environment information on its own travel path during the travel process, and based on the three-dimensional environment information, identifies the obstacle areas and types present on the travel path of the self-mobile device. For different area types, different travel control is adopted in a targeted manner, and the travel control method of this application is adopted to improve the obstacle avoidance performance of the mobile device.
  • the embodiments of the present application also provide a computer-readable storage medium storing a computer program.
  • the computer-readable storage medium stores a computer program
  • the computer program is executed by one or more processors 902
  • the one or more processors 902 are caused to perform the steps in the method embodiment shown in FIG.
  • the self-mobile device may be a robot, an unmanned vehicle, or the like.
  • FIG. 10 is a structural block diagram of a robot provided by an exemplary embodiment of the present application. As shown in FIG. 10, the robot includes: a mechanical body 1001; one or more processors 1003 and one or more memories 1004 storing computer instructions are provided on the mechanical body 1001. In addition, a sensor 1002 is also provided on the mechanical body 1001. The sensor 1002 is an area solid-state lidar 1002. During the robot working process, it is used to collect three-dimensional environmental information on the travel path of the mobile device.
  • the mechanical body 1001 is also provided with some basic components of the robot, such as audio components, power components, odometers, driving components, and so on.
  • An audio component the audio component, may be configured to output and / or input audio signals.
  • the audio component includes a microphone (MIC).
  • the microphone When the device where the audio component is located is in an operation mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal.
  • the received audio signal may be further stored in the memory or sent via the communication component.
  • the audio component further includes a speaker for outputting audio signals.
  • the sensor 1002 may also include a dry humidity sensor 1002 and the like.
  • the driving assembly may include a driving wheel, a driving motor, a universal wheel, and the like.
  • the cleaning assembly may include a cleaning motor, a cleaning brush, a dusting brush, a dust suction fan, and the like.
  • the audio component, the sensor 1002, the one or more processors 1003, and the one or more memories 1004 can be disposed inside the mechanical body 1001 or on the surface of the mechanical body 1001.
  • the mechanical body 1001 is an execution mechanism on which a robot completes a job task, and can perform operations specified by the processor 1003 in a certain environment.
  • the mechanical body reflects the appearance of the robot to a certain extent.
  • the appearance of the robot is not limited, for example, it may be a circle, an ellipse, a triangle, a convex polygon, or the like.
  • the one or more memories 1004 are mainly used to store computer programs that can be executed by one or more processors 1003, so that the one or more processors 1004 can perform new control operations on the mobile device. In addition to storing computer programs, one or more memories 1004 may also be configured to store various other data to support operations on the robot.
  • One or more processors 1003 can be regarded as a control system of the robot, and can be used to execute computer programs stored in one or more memories 1004 to perform new control operations on the mobile device.
  • the processor 1003 stores, for example, a computer program in one or more memories 1004, and the one or more processors 1003 can execute the computer program and can be used for:
  • Three-dimensional environment information collected from the traveling path of the mobile device
  • the traveling control of the mobile device is performed for the obstacle area.
  • one or more processors 1002 based on the three-dimensional environment information, identify the obstacle area and its type existing on the travel path of the mobile device, and are used to: based on the three-dimensional environment information, identify the abnormal area on the travel path of the mobile device As an obstacle area; according to the abnormal state of the obstacle area relative to the working plane, determine the type of the obstacle area.
  • one or more processors 1002 determine the type of the obstacle area according to the abnormal state of the obstacle area relative to the work plane, and are used to: if there is an obstacle protruding from the work plane in the obstacle area, determine the obstacle area as a pending Overturn the area; if there is a sinking space below the working plane in the obstacle area, determine the obstacle area as the area to be lowered; if there is a gap in the obstacle area at the same height as the work plane, determine the obstacle area as the area to be traversed.
  • one or more processors 1002 according to the type of the obstacle area, control the travel of the self-mobile device for the obstacle area, and are used to: according to the type of the obstacle area, combine the relative size relationship between the self-mobile device and the obstacle area, Control the travel of the mobile device for the obstacle area.
  • one or more processors 1002 according to the type of the obstacle area, combined with the relative size relationship between the self-mobile device and the obstacle area, perform travel control on the self-mobile device for the obstacle area, and are used to: Calculate the height of the obstacle in the area to be overturned according to the relationship between the height of the obstacle and the first threshold, and control the travel of the self-mobile device for the area to be overturned, where the first threshold is less than or equal to the The height of the fuselage from the working plane.
  • the one or more processors 1002 perform travel control on the self-mobile device for the area to be overturned, and are used to: if the height of the obstacle is greater than or equal to If it is equal to the first threshold, the mobile device is controlled to perform the obstacle avoidance operation; if the height of the obstacle is less than the first threshold, the mobile device is controlled to roll over the area to be overturned.
  • one or more processors 1002 perform travel control on the self-mobile device for the obstacle area, and are used to: Calculate the depth of the sinking space in the area to be lowered; based on the relationship between the depth of the sinking space and the second threshold, perform travel control on the mobile device for the area to be lowered, where the second threshold is less than It is equal to the height of the mobile device from the working plane.
  • the one or more processors 1002 perform travel control on the self-mobile device for the area to be lowered, which is used to: if the depth of the sinking space is greater than or equal to the If the threshold is two, the obstacle avoidance operation is performed; if the depth of the sinking space is less than the second threshold, the control jumps from the mobile device to the area to be jumped to continue working.
  • one or more processors 1002 perform travel control on the self-mobile device for the obstacle area, and are used to: if the type of the obstacle area is For the area to be traversed, calculate the height and width of the gap in the area to be traversed; according to the relationship between the height and width of the gap and the height of the body of the self-mobile device, the travel control of the self-mobile device is performed for the area to be traversed.
  • the one or more processors 1002 based on the relationship between the height and width of the gap and the height of the body of the mobile device, control the travel of the mobile device for the area to be traversed, and are used to: The width of the body of the mobile device, and the height of the gap is greater than the height of the body of the mobile device, then the self-mobile device is controlled to continue to travel through the area to be traversed according to the travel path; if the width of the gap is less than or equal to the width of the body of the mobile device If the height of the gap is less than or equal to the height of the body of the mobile device, at least one of the conditions is met, then the obstacle avoidance operation is performed.
  • the self-mobile device collects three-dimensional environmental information on its own travel path during travel, and identifies the obstacle areas and types present on the travel path of the self-mobile device based on the three-dimensional environmental information.
  • the type of the area is targeted to adopt different travel controls, and the travel control method of this application is adopted to improve the obstacle avoidance performance of the mobile device.
  • the embodiments of the present application also provide a computer-readable storage medium storing a computer program.
  • the computer-readable storage medium stores a computer program
  • the computer program is executed by one or more processors 1002
  • the one or more processors 1002 are caused to perform the steps in the method embodiment shown in FIG.
  • These computer program instructions may also be stored in a computer readable memory that can guide a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, the instructions The device implements the functions specified in one block or multiple blocks of the flowchart one flow or multiple flows and / or block diagrams.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operating steps are performed on the computer or other programmable device to produce computer-implemented processing, which is executed on the computer or other programmable device
  • the instructions provide steps for implementing the functions specified in one block or multiple blocks of the flowchart one flow or multiple flows and / or block diagrams.
  • the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.
  • processors CPUs
  • input / output interfaces output interfaces
  • network interfaces network interfaces
  • memory volatile and non-volatile memory
  • Memory may include non-permanent memory in computer-readable media, random access memory
  • RAM random access memory
  • ROM read-only memory
  • flash RAM flash memory
  • Computer-readable media including permanent and non-permanent, removable and non-removable media, can store information by any method or technology.
  • the information may be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, read-only compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, Magnetic tape cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media can be used to store information that can be accessed by computing devices.
  • computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

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Abstract

一种行进控制的方法、设备及存储介质，所述方法包括：自移动设备在行进过程中采集自身行进路径上的三维环境信息（S101），基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型（S102），自移动设备对于不同的区域类型，针对性地采取不同的行进控制（S103）。采用上述行进控制的方法，提高自移动设备的避障性能。

Description

行进控制的方法、设备及存储介质
交叉引用
本申请引用于2018年10月22日递交的名称为“行进控制的方法、设备及存储介质”的第201811232109.2号中国专利申请，其通过引用被全部并入本申请。
技术领域
本申请涉及人工智能技术领域，尤其涉及一种行进控制的方法、设备及存储介质。
背景技术
扫地机器人在清扫地面过程中，需要对障碍物进行避让，以便更好的进行清洁工作。
扫地机器人的避障功能一般由红外、激光、超声波等距离传感器和弹簧挡板配合实现，距离传感器检测到前方有障碍物或者弹簧挡板碰触障碍物后，机器将按照避障的控制指令返回或绕行。
发明内容
本申请的多个方面提供一种自移动设备行进控制的方法，解决现有技术中存在的自移动设备对障碍物判断不准确的问题，提高自移动设备的避障能力。
本申请实施例提供一种行进控制的方法，适用于自移动设备，包括：
采集自移动设备行进路径上的三维环境信息；
基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
本申请实施例还提供一种自移动设备，包括：机械本体，所述机械本体上设有面阵固态激光雷达，一个或多个处理器，以及一个或多个存储计算机程序的存储器；
所述面阵固态激光雷达，用于采集自移动设备行进路径上的三维环境信息；
所述一个或多个处理器，用于执行所述计算机程序，以用于：
基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
本申请实施例还提供一种存储有计算机程序的计算机可读存储介质，当所述计算机程序被一个或多个处理器执行时，致使所述一个或多个处理器执行包括以下的动作：
采集自移动设备行进路径上的三维环境信息；
基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
在本申请一些示例性实施例中，自移动设备在行进过程中采集自身行进路径上的三维环境信息，基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型，自移动设备对于不同的区域类型，针对性地采取不同的行进控制，采用本申请行进控制的方法，提高自移动设备的避障性能。
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为本申请示例性实施例提供的一种行进控制的方法的方法流程图；
图2为本申请示例性实施例扫地机器人前方存在门槛石的示意图；
图3为本申请示例性实施例扫地机器人前方存在上级台阶的示意图；
图4为本申请示例性实施例扫地机器人前方存在向上斜坡的示意图；
图5为本申请示例性实施例对扫地机器人高度形成约束的间隙的示意图；
图6为本申请示例性实施例对扫地机器人宽度形成约束的间隙的示意图；
图7为本申请示例性实施例扫地机器人前方存在下级台阶的示意图；
图8为本申请示例性实施例扫地机器人前方存在向下斜坡的示意图；
图9为本申请示例性实施例提供的一种自移动设备的结构框图；
图10为本申请示例性实施例提供的一种机器人的结构框图。
具体实施方式
为使本申请的目的、技术方案和优点更加清楚，下面将结合本申请具体实施例及相应的附图对本申请技术方案进行清楚、完整地描述。显然，所描述的实施例仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
家用机器人在实际应用中，需要通对场景内的障碍物信息进行量测和建图，从而进行有效的避障与路径规划。基于传感器的不同，现有机器人的避障方法主要有两种：LDS技术和Vslam技术。在建图不完整情况下，遇到未知障碍物时，机器需要进行动态避障，LDS仅能探测一个平面内的障碍物信息，垂直方向无法测量，易造成机身经常钻入缝隙较窄的柜底、床底等区域并卡死，造成不必要的动作。Vslam获取到的数据中缺乏地标信息，从而引起机器人对障碍物判断不准确。
针对上述现有扫地机器人在清洁地面工作中存在的问题，在本申请一些示例性实施例中，自移动设备在行进过程中采集自身行进路径上的三维环境信息，基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型，自移动设备对于不同的区域类型，针对性地采取不同的行进控制，采用本申请行进控制的方法，提高自移动设备的避障性能。
以下结合附图，详细说明本申请各实施例提供的技术方案。
图1为本申请示例性实施例提供的一种行进控制的方法的方法流程图，如图1所示，该方法包括：
S101：采集自移动设备行进路径上的三维环境信息；
S102：基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
S103：根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
本申请实施例的上述方法的执行主体可以为自移动设备，如无人车、机器人等，且对机器人、无人车的类型不作限定，机器人可以为为扫地机器人，跟随机器人，迎宾机器人等。不同的设备针对不同的工作环境获取相应工作环境中的三维环境信息，例如，扫地机器人在对住户家庭清扫过程中，可在行进过程中获取客厅、厨房、卫生间、卧式等区域的三维环境图像；商场导购机器人在对客户进行导购的过程中，可在行进过程中获取人行通道、商铺等各区域的三维环境图像；跟随机器人在跟随目标的过程中，可在行进过程中获取跟随目标以及前进过程中的周围环境的三维环境信息。
在本实施例中，通过在自移动设备上安装面阵固态激光雷达，实时对自移动设备行进路径上的三维环境信息进行采集。面阵固态激光雷达作为一种低成本、固态化、小型化的新型传感器，能够快捷、准确获取大量三维信息，很好的满足了定位和建图过程中对信息量的需求，面阵激光雷达可以在距离障碍物一定距离时，探测前方维障碍物形成的约束空间是否可以通过，避免不必要的探索与碰撞。面阵固态激光雷达运用衍射分光元件对发射激光光束进行n*n分光，单个分光运用三角测距原理，即发射激光经扩束镜准直后照 射到目标表面，接收到系统受到的目标回波信号，通过位置敏感原价对散射光斑中心位置进行测量，对多束分光信息进行融合处理，即可得到三维数据信息。
在上述实施例中，基于面阵激光雷达采集自移动设备行进路径上的三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型。可选地，基于采集的自移动设备行进路径上的三维环境信息，识别出自移动设备行进路径上的异常区域，作为障碍区域；根据障碍区域相对工作平面的异常状态，确定障碍区域的类型。本实施例在距离障碍物一定距离时，确定障碍区域以及障碍区域的类型，针对不同类型的障碍区域对自移动设备进行不同的行进控制。
在上述及下述实施例中，障碍区域的类型可以包括下列三种类型：待翻越区域，待下跃区域和待穿越区域。下列说明根据障碍区域相对工作平面的异常状态，确定每种障碍区域的类型的方式。
确定待翻越区域的方式：若障碍区域中存在凸起于工作平面的障碍物，且障碍物上没有间隙，确定障碍区域为待翻越区域。即，障碍区域中存在有可能需要自移动设备翻越行走的障碍物，例如：门槛石(图2为本申请示例性实施例扫地机器人前方存在门槛石的示意图，箭头所指方向为扫地机器人的行进方向)，上级台阶(图3为本申请示例性实施例扫地机器人前方存在上级台阶的示意图，箭头所指方向为扫地机器人的行进方向)和向上斜坡(图4为本申请示例性实施例扫地机器人前方存在向上斜坡的示意图，箭头所指方向为扫地机器人的行进方向)等。
确定待下跃区域的方式：待下跃区域若障碍区域中存在低于工作平面的下沉空间，确定障碍区域为待下跃区域。即，障碍区域中存在有可能需要自移动设备跃下以进入另一工作平面的下沉空间，例如：下级台阶(图7为本申请示例性实施例扫地机器人前方存在下级台阶的示意图，箭头所指方向为扫地机器人的行进方向)和向下斜坡(图8为本申请示例性实施例扫地机器人前方存在向下斜坡的示意图，箭头所指方向为扫地机器人的行进方向)等。
确定待穿越区域的方式：若障碍区域中存在与工作平面同一高度的间隙，确定障碍区域为待穿越区域。即，障碍区域的工作平面上存在有可能需要自移动设备穿越行走的间隙，其中，间隙包括对自移动设备高度形成约束的间隙和对自移动设备宽度或者长度形成约束的间隙(图5为本申请示例性实施例对扫地机器人高度形成约束的间隙)。对自移动设备高度形成约束的间隙，例如：床、柜、桌、椅、茶几、沙发等底部，对自移动设备宽度或者长度形成约束的间隙包括狭窄走廊间隙(图6为本申请示例性实施例对扫地机器人宽度形成约束的间隙)，例如：各类家具之间形成的间隙(沙发和茶几之间、床和柜之间、桌和椅之间等)，家具自身构造形成的间隙(椅子腿，桌子腿之间等)。
在自移动设备的实际工作过程中，可能会存在待翻越区域、待下跃区域、待穿越区域中的一种障碍区域或者任意两种障碍区域或者三种障碍区域的组合，例如，扫地机器人在清扫住户家庭的过程中，当扫地机器人从客厅进入卫生间时，卫生间的门口处设有凸起设置的门槛石，且卫生间的地面低于客厅的地面，此时存在待翻越区域和待下跃区域两种障碍区域，显然，还可能存在其他障碍区域的组合。
在识别自移动行进路径上存在的障碍区域及其障碍区域的类型后，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制。下面说明针对不同类型的障碍区域，对自移动设备进行相应的行进控制的方式。
当障碍区域的类型为待翻越区域时，计算待翻越区域内的障碍物的高度；根据障碍物的高度与第一阈值的关系，针对待翻越区域对自移动设备进行行进控制。可选地，若障碍物的高度大于或等于第一阈值，则控制自移动设备执行避障操作；若障碍物的高度小于第一阈值，则控制自移动设备翻越待翻越区域。需要说明的是，第一阈值小于等于自移动设备的机身距离工作平面的高度自移动设备执行避障操作可以为自移动设备绕开障碍物行走。
需要说明的是，当前方障碍物是上行斜面时，可以采用斜面的高度与第 一阈值的关系，针对待翻越区域对自移动设备进行行进控制。也可以采用斜面的倾斜角度与第三阈值的关系，针对待翻越区域对自移动设备进行行进控制。还可以为结合斜面的高度与第一阈值的关系、斜面的倾斜角度与第三阈值的关系，针对待翻越区域对自移动设备进行行进控制。具体实施方式结合前述实施例的具体实施例描述的部分简单变形即可。
当自移动设备需要翻越待翻越区域时，为了提高自移动设备翻越障碍物的成功率，需要控制自移动设备加快速度翻越待翻越区域。根据自移动设备预设的行进速度和障碍物的高度，计算自移动设备翻越待翻越区域所需的第一速度；控制自移动设备沿行进路径以第一速度翻越待翻越区域。可选地，第一速度为障碍物的高度、自移动设备预设的行进速度和预设的第一速率系数的乘积。即第一速度V1＝h*a1*v，其中，h为障碍物高度；a1为根据实验测得的速率系数；v为自移动设备正常工作时的前进速度。本申请实施例根据障碍物高度适应性调整自移动设备的前进速度，自移动设备加速翻越障碍物，增加翻越流畅性。显而易见的是，自移动设备翻越障碍物的速度也可以采用其他的计算方式，自移动设备也可以按照原先的速度翻越障碍物。
当障碍区域的类型为待下跃区域时，计算待下跃区域内的下沉空间的深度；根据下沉空间的深度与第二阈值的关系，针对待下跃区域对自移动设备进行行进控制。可选地，若下沉空间的深度大于等于第二阈值，则执行避障操作；若下沉空间的深度小于第二阈值，则控制自移动设备下跃至待下跃区域继续工作。需要说明的是，本实施例中，第二阈值小于等于自移动设备的机身距离工作平面的高度。特别地，可以根据下沉空间的三维信息与自移动设备的三维信息的关系，针对待下跃区域对自移动设备进行行进控制。可选地，先行计算下沉空间的横截面积和自移动设备的横截面积的大小关系，接着再计算下沉空间的深度和第二阈值的大小关系，确定自移动设备是否执行避障操作。例如，当前方是一个相对自移动设备小很多的小坑时，则控制自移动设备按照预先设定的行进路径继续行进，当前方是一个比自移动设备很多的下沉空间时，接着再计算下沉空间的深度和第二阈值的大小关系，确定 自移动设备执行避障操作或者下跃至下沉空间继续工作。自移动设备执行避障操作可以为自移动设备绕开下沉空间行走。
需要说明的是，当前方下沉空间是下行斜面时，可以采用斜面的高度与第二阈值的关系，针对待翻越区域对自移动设备进行行进控制。也可以采用斜面的倾斜角度与第四阈值的关系，针对待翻越区域对自移动设备进行行进控制。还可以为结合斜面的高度与第二阈值的关系、斜面的倾斜角度与第四阈值的关系，针对待翻越区域对自移动设备进行行进控制。具体实施方式结合前述实施例的具体实施例描述的部分简单变形即可。
当自移动设备需要下跃至待下跃区域时，为了提高自移动设备下跃至待下跃区域的平稳性，需要控制自移动设备减小速度下跃至待下跃区域。根据自移动设备的预设的行进速度和下沉空间的深度，计算自移动设备下跃至待下跃区域的第二速度；自移动设备沿行进路径以第二速度下跃至待下跃区域。可选地，第二速度为下沉空间的深度的倒数、自移动设备预设的行进速度和预设的第二速率系数的乘积。即第二速度V2＝(1/d)*a2*v，其中，d为下沉空间的深度，a2为根据实验测得的速率系数，v为自移动设备正常工作时的前进速度。本申请实施例根据下沉空间的深度适应性调整自移动设备的前进速度，自移动设备减速下跃至下沉空间继续工作，增加自移动设备的动作流畅性。自移动设备下跃至下沉空间的速度也可以采用其他的计算方式，自移动设备也可以按照原先的速度下跃至下沉空间。
当障碍区域的类型为待穿越区域时，计算待穿越区域内的间隙的高度和宽度；根据间隙的高度和宽度与自移动设备的机身高度的关系，针对待穿越区域对自移动设备进行行进控制。可选地，若间隙的宽度大于自移动设备的机身宽度，且间隙的高度大于自移动设备的机身高度，则控制自移动设备按照行进路径继续行进穿过待穿越区域；若在间隙的宽度小于等于自移动设备的机身宽度、间隙的高度小于等于自移动设备的机身高度中的至少一个条件成立，则执行避障操作。即间隙的空间若足够允许自移动设备通过，则自移动设备穿过间隙，反之，则控制自移动设备执行避障操作。
当自移动设备需要穿越待穿越区域时，为了提高自移动设备穿越间隙的成功率，可以控制自移动设备加快速度穿越待穿越区域。根据自移动设备的预设的行进速度和间隙的宽度，计算自移动设备按照行进路径继续行进穿过待穿越区域的第三速度；自移动设备沿行进路径以第三速度继续行进穿过待穿越区域。可选地，第三速度为间隙的宽度、自移动设备预设的行进速度和预设的第三速率系数的乘积。即，第三速度V3＝b*a3*v，其中，b为间隙的宽度或者高度，a3为根据实验测得的速率系数；v为自移动设备正常工作时的前进速度。本申请实施例根据间隙的高度以及宽度信息适应性调整自移动设备的前进速度，自移动设备加速通过间隙，增加自移动设备的动作流畅性。自移动设备穿越间隙的速度也可以采用其他的计算方式，自移动设备也可以按照原先的速度穿越间隙。
下面结合不同场景的实施例对本申请行进控制的方法作出说明。
应用场景1：在无人车行驶场景中，无人车利用安装于无人车车身上的面阵固态激光雷达，实时对行进路径上的路面信息进行采集。当无人车行进路径上的路面上存在倒放在路面上的树木时，无人车通过面阵固态激光雷达获取前方路面上的树木的三维信息，经过分析得到路面上存在异常状态，确定路面前方区域为障碍区域，且障碍区域中存在凸起于路面的障碍物，确定障碍区域为待翻越区域，计算倒放在路面上的树木的高度，若倒放在路面上的树木的高度大于或者等于无人车的车身的高度，则控制无人车后退并重新规划行进路径，若倒放在路面上的树木的高度小于无人车的车身的高度，则控制无人车翻越树木。当无人车需要翻越树木时，为了提高无人车更加顺畅的翻越树木，控制无人车加快速度翻越前面路面上的树木，其中，无人车翻越树木的速度为为倒放的树木的高度、无人车预设的行进速度和预设的速率系数的乘积。
应用场景2：扫地机器人清洁地面场景中，扫地机器人利用安装于机械本体前方的面阵固态激光雷达，实时对行进路径上的地面信息进行采集，获取地面上的三维信息，当扫地机器人前方的行进路径上存在椅子时，扫地机器 人通过面阵固态激光雷达获取前方路面上的椅子的三维信息，经过分析得到前面地面上存在异常状态，确定地面前方区域为障碍区域，障碍区域中存在椅子下方形成的间隙，确定障碍区域为待穿越区域，计算椅子下方间隙的高度和宽度，若椅子下方的间隙的宽度大于扫地机器人的宽度，且椅子下方的间隙的高度大于扫地机器人安装控制扫地机器人按照行进路径继续行进进入椅子下方继续进行清扫工作，若椅子下方的间隙的宽度小于等于扫地机器人的宽度、间隙的高度小于等于扫地机器人的总高度中的至少一个条件成立，则扫地机器人绕开椅子继续清扫工作。当椅子下方的间隙的高度远大于扫地机器人的总高度，椅子下方的宽度大于扫地机器人的宽度时，扫地机器人需要穿越椅子下方的间隙，为了提高扫地机器人穿越间隙的成功率，可以控制扫地机器人加快速度穿越椅子下方的间隙。且扫地机器人穿过椅子下方的间隙的速度为间隙的宽度、扫地机器人预设的行进速度和预设的速率系数的乘积。
应用场景3：在商场导购机器人的导购场景中，商场导购机器人利用安装于机械本体上的面阵固态激光雷达，实时对行进路径上的地面信息进行采集，获取地面上的三维信息，当商场导购机器人的前方的行进路径上存在下级台阶时，商场导购机器人通过面阵固态激光雷达获取前方路面上的下级台阶的三维信息，经过分析得到前面地面上存在异常状态，确定地面前方区域为障碍区域，障碍区域中存在低于地面的下沉空间，确定障碍区域为待下跃区域，计算下沉空间的深度，若下沉空间的深度大于等于导购机器人的机身高度，则导购机器人进行绕行；若下沉空间的深度小于导购机器人的机身高度，则导购机器人下跃至台阶下方的地面继续工作。当导购机器人需要下跃至待下跃区域时，为了提高导购机器人下跃至台阶下方的下沉空间的平稳性，需要控制导购机器人减小速度下跃至台阶下方的下沉空间。导购机器人下跃至台阶下方的下沉空间的速度为下沉空间的深度的倒数、导购机器人预设的行进速度和预设的速率系数的乘积。
图9为本申请示例性实施例提供的一种自移动设备的结构框图。该自移 动设备包括一个或多个处理器902和一个或多个存储计算机程序的存储器903和传感器905。该传感器905为面阵固态激光雷达905，用于采集自移动设备行进路径上的三维环境信息；还可以包括音频组件901、电源组件904等必要组件。一个或多个处理器902，用于执行计算机程序，以用于：
采集自移动设备行进路径上的三维环境信息；
基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
可选地，一个或多个处理器902，基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型，用于：基于三维环境信息，识别自移动设备行进路径上的异常区域作为障碍区域；根据障碍区域相对工作平面的异常状态，确定障碍区域的类型。
可选地，一个或多个处理器902，根据障碍区域相对工作平面的异常状态，确定障碍区域的类型，用于：若障碍区域中存在凸起于工作平面的障碍物，确定障碍区域为待翻越区域；若障碍区域中存在低于工作平面的下沉空间，确定障碍区域为待下跃区域；若障碍区域中存在与工作平面同一高度的间隙，确定障碍区域为待穿越区域。
可选地，一个或多个处理器902，根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制，用于：根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制。
可选地，一个或多个处理器902，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制，用于：若障碍区域的类型为待翻越区域，计算待翻越区域内的障碍物的高度；根据障碍物的高度与第一阈值的关系，针对待翻越区域对自移动设备进行行进控制，其中，第一阈值小于等于自移动设备的机身距离工作平面的高度。
可选地，一个或多个处理器902，根据障碍物的高度与自移动设备的机身高度的关系，针对待翻越区域对自移动设备进行行进控制，用于：若障碍物 的高度大于或等于第一阈值，则控制自移动设备执行避障操作；若障碍物的高度小于第一阈值，则控制自移动设备翻越待翻越区域。
可选地，一个或多个处理器902，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制，用于：若障碍区域的类型为待下跃区域，计算待下跃区域内的下沉空间的深度；根据下沉空间的深度与第二阈值的关系，针对待下跃区域对自移动设备进行行进控制，其中，第二阈值小于等于自移动设备的机身距离工作平面的高度。
可选地，一个或多个处理器902，根据下沉空间的深度与第二阈值关系，针对待下跃区域对自移动设备进行行进控制，用于：若下沉空间的深度大于等于第二阈值，则执行避障操作；若下沉空间的深度小于第二阈值，则控制自移动设备下跃至待下跃区域继续工作。
可选地，一个或多个处理器902，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制，用于：若障碍区域的类型为待穿越区域，计算待穿越区域内的间隙的高度和宽度；根据间隙的高度和宽度与自移动设备的机身高度的关系，针对待穿越区域对自移动设备进行行进控制。
可选地，一个或多个处理器902，根据间隙的高度和宽度与自移动设备的机身高度的关系，针对待穿越区域对自移动设备进行行进控制，用于：若间隙的宽度大于自移动设备的机身宽度，且间隙的高度大于自移动设备的机身高度，则控制自移动设备按照行进路径继续行进穿过待穿越区域；若在间隙的宽度小于等于自移动设备的机身宽度、间隙的高度小于等于自移动设备的机身高度中的至少一个条件成立，则执行避障操作。
在本申请自移动设备实施例中，自移动设备在行进过程中采集自身行进路径上的三维环境信息，基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型，自移动设备对于不同的区域类型，针对性地采取不同的行进控制，采用本申请行进控制的方法，提高自移动设备的避障性能。
相应地，本申请实施例还提供一种存储有计算机程序的计算机可读存储 介质。当计算机可读存储介质存储计算机程序，且计算机程序被一个或多个处理器902执行时，致使一个或多个处理器902执行相应图1所示方法实施例中的各步骤。
上述自移动设备可以为机器人、无人车等。图10为本申请示例性实施例提供的一种机器人的结构框图。如图10所示，该机器人包括：机械本体1001；机械本体1001上设有一个或多个处理器1003和一个或多个存储计算机指令的存储器1004。除此之外，机械本体1001上还设有传感器1002，该传感器1002为面阵固态激光雷达1002，在机器人工作过程中，用于采集自移动设备行进路径上的三维环境信息。
机械本体1001上除了设有一个或多个处理器1003以及一个或多个存储器1004之外，还设置有机器人的一些基本组件，例如音频组件、电源组件、里程计、驱动组件等等。音频组件，该音频组件，可被配置为输出和/或输入音频信号。例如，音频组件包括一个麦克风(MIC)，当音频组件所在设备处于操作模式，如呼叫模式、记录模式和语音识别模式时，麦克风被配置为接收外部音频信号。所接收的音频信号可以被进一步存储在存储器或经由通信组件发送。在一些实施例中，音频组件还包括一个扬声器，用于输出音频信号。传感器1002还可以包括干湿度传感器1002等。可选地，驱动组件可以包括驱动轮、驱动电机、万向轮等。可选地，清扫组件可以包括清扫电机、清扫刷、起尘刷、吸尘风机等。不同机器人所包含的这些基本组件以及基本组件的构成均会有所不同，本申请实施例仅是部分示例。
值得说明的是，音频组件、传感器1002、一个或多个处理器1003、一个或多个存储器1004可设置于机械本体1001内部，也可以设置于机械本体1001的表面。
机械本体1001是机器人赖以完成作业任务的执行机构，可以在确定的环境中执行处理器1003指定的操作。其中，机械本体一定程度上体现了机器人的外观形态。在本实施例中，并不限定机器人的外观形态，例如可以是圆形、椭圆形、三角形、凸多边形等。
一个或多个存储器1004，主要用于存储计算机程序，该计算机程序可被一个或多个处理器1003执行，致使一个或多个处理器1004可以对自移动设备进行新进控制操作。除了存计算机程序之外，一个或多个存储器1004还可被配置为存储其它各种数据以支持在机器人上的操作。
一个或多个处理器1003，可以看作是机器人的控制系统，可用于执行一个或多个存储器1004中存储的计算机程序，以对自移动设备进行新进控制操作。
处理器1003例如，一个或多个存储器1004中存储计算机程序，一个或多个处理器1003可以执行计算机程序，可用于：
采集自移动设备行进路径上的三维环境信息；
基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
可选地，一个或多个处理器1002，基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型，用于：基于三维环境信息，识别自移动设备行进路径上的异常区域作为障碍区域；根据障碍区域相对工作平面的异常状态，确定障碍区域的类型。
可选地，一个或多个处理器1002，根据障碍区域相对工作平面的异常状态，确定障碍区域的类型，用于：若障碍区域中存在凸起于工作平面的障碍物，确定障碍区域为待翻越区域；若障碍区域中存在低于工作平面的下沉空间，确定障碍区域为待下跃区域；若障碍区域中存在与工作平面同一高度的间隙，确定障碍区域为待穿越区域。
可选地，一个或多个处理器1002，根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制，用于：根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制。
可选地，一个或多个处理器1002，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制， 用于：若障碍区域的类型为待翻越区域，计算待翻越区域内的障碍物的高度；根据障碍物的高度与第一阈值的关系，针对待翻越区域对自移动设备进行行进控制，其中，第一阈值小于等于自移动设备的机身距离工作平面的高度。
可选地，一个或多个处理器1002，根据障碍物的高度与自移动设备的机身高度的关系，针对待翻越区域对自移动设备进行行进控制，用于：若障碍物的高度大于或等于第一阈值，则控制自移动设备执行避障操作；若障碍物的高度小于第一阈值，则控制自移动设备翻越待翻越区域。
可选地，一个或多个处理器1002，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制，用于：若障碍区域的类型为待下跃区域，计算待下跃区域内的下沉空间的深度；根据下沉空间的深度与第二阈值的关系，针对待下跃区域对自移动设备进行行进控制，其中，第二阈值小于等于自移动设备的机身距离工作平面的高度。
可选地，一个或多个处理器1002，根据下沉空间的深度与第二阈值的关系，针对待下跃区域对自移动设备进行行进控制，用于：若下沉空间的深度大于等于第二阈值，则执行避障操作；若下沉空间的深度小于第二阈值，则控制自移动设备下跃至待下跃区域继续工作。
可选地，一个或多个处理器1002，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制，用于：若障碍区域的类型为待穿越区域，计算待穿越区域内的间隙的高度和宽度；根据间隙的高度和宽度与自移动设备的机身高度的关系，针对待穿越区域对自移动设备进行行进控制。
可选地，一个或多个处理器1002，根据间隙的高度和宽度与自移动设备的机身高度的关系，针对待穿越区域对自移动设备进行行进控制，用于：若间隙的宽度大于自移动设备的机身宽度，且间隙的高度大于自移动设备的机身高度，则控制自移动设备按照行进路径继续行进穿过待穿越区域；若在间隙的宽度小于等于自移动设备的机身宽度、间隙的高度小于等于自移动设备 的机身高度中的至少一个条件成立，则执行避障操作。
在本申请机器人实施例中，自移动设备在行进过程中采集自身行进路径上的三维环境信息，基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型，自移动设备对于不同的区域类型，针对性地采取不同的行进控制，采用本申请行进控制的方法，提高自移动设备的避障性能。
相应地，本申请实施例还提供一种存储有计算机程序的计算机可读存储介质。当计算机可读存储介质存储计算机程序，且计算机程序被一个或多个处理器1002执行时，致使一个或多个处理器1002执行相应图1所示方法实施例中的各步骤。
本发明是参照根据本发明实施例的方法、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。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输 出接口、网络接口和内存。
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器
(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、商品或者设备中还存在另外的相同要素。
以上所述仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。

Claims (13)

  1. 一种行进控制的方法，适用于自移动设备，其特征在于，所述方法包括：
    采集自移动设备行进路径上的三维环境信息；
    基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
    根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
  2. 根据权利要求1所述的方法，其特征在于，基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型，包括：
    基于三维环境信息，识别自移动设备行进路径上的异常区域作为所述障碍区域；
    根据障碍区域相对工作平面的异常状态，确定障碍区域的类型。
  3. 根据权利要求2所述的方法，其特征在于，根据障碍区域相对工作平面的异常状态，确定障碍区域的类型，包括：
    若障碍区域中存在凸起于工作平面的障碍物，确定障碍区域为待翻越区域；
    若障碍区域中存在低于工作平面的下沉空间，确定障碍区域为待下跃区域；
    若障碍区域中存在与工作平面同一高度的间隙，确定障碍区域为待穿越区域。
  4. 根据权利要求1所述的方法，其特征在于，根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制，包括：
    根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制。
  5. 根据权利要求4所述的方法，其特征在于，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行 行进控制，包括：
    若障碍区域的类型为待翻越区域，计算待翻越区域内的障碍物的高度；
    根据障碍物的高度与第一阈值的关系，针对所述待翻越区域对自移动设备进行行进控制，其中，第一阈值小于等于自移动设备的机身距离工作平面的高度。
  6. 根据权利要求5所述的方法，其特征在于，根据障碍物的高度与第一阈值的关系，针对所述待翻越区域对自移动设备进行行进控制，包括：
    若障碍物的高度大于或等于第一阈值，则控制自移动设备执行避障操作；
    若障碍物的高度小于第一阈值，则控制自移动设备翻越待翻越区域。
  7. 根据权利要求4所述的方法，其特征在于，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制，包括：
    若障碍区域的类型为待下跃区域，计算待下跃区域内的下沉空间的深度；
    根据下沉空间的深度与第二阈值的关系，针对所述待下跃区域对自移动设备进行行进控制，其中，第二阈值小于等于自移动设备的机身距离工作平面的高度。
  8. 根据权利要求7所述的方法，其特征在于，根据下沉空间的深度与第二阈值的关系，针对所述待下跃区域对自移动设备进行行进控制，包括：
    若下沉空间的深度大于等于第二阈值，则执行避障操作；
    若下沉空间的深度小于第二阈值，则控制自移动设备下跃至待下跃区域继续工作。
  9. 根据权利要求4所述的方法，其特征在于，根据障碍区域的类型，结合自移动设备与障碍区域的相对大小关系，针对障碍区域对自移动设备进行行进控制，包括：
    若障碍区域的类型为待穿越区域，计算待穿越区域内的间隙的高度和宽度；
    根据间隙的高度和宽度与自移动设备的机身高度的关系，针对所述待穿 越区域对自移动设备进行行进控制。
  10. 根据权利要求9所述的方法，其特征在于，根据间隙的高度和宽度与自移动设备的机身高度的关系，针对所述待穿越区域对自移动设备进行行进控制，包括：
    若间隙的宽度大于自移动设备的机身宽度，且间隙的高度大于自移动设备的机身高度，则控制自移动设备按照行进路径继续行进穿过待穿越区域；
    若在间隙的宽度小于等于自移动设备的机身宽度、间隙的高度小于等于自移动设备的机身高度中的至少一个条件成立，则执行避障操作。
  11. 一种自移动设备，其特征在于，包括：机械本体，所述机械本体上设有面阵固态激光雷达，一个或多个处理器，以及一个或多个存储计算机程序的存储器；
    所述面阵固态激光雷达，用于采集自移动设备行进路径上的三维环境信息；
    所述一个或多个处理器，用于执行所述计算机程序，以用于：
    基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
    根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
  12. 根据权利要求11所述的自移动设备，其特征在于，所述自移动设备为扫地机器人，所述面阵固态激光雷达设于机械本体的前方。
  13. 一种存储有计算机程序的计算机可读存储介质，其特征在于，当所述计算机程序被一个或多个处理器执行时，致使所述一个或多个处理器执行包括以下的动作：
    采集自移动设备行进路径上的三维环境信息；
    基于三维环境信息，识别自移动设备行进路径上存在的障碍区域及其类型；
    根据障碍区域的类型，针对障碍区域对自移动设备进行行进控制。
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