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CN112232201A - Vehicle obstacle avoidance route planning method, vehicle obstacle avoidance method, computer readable storage medium and AGV car - Google Patents

Vehicle obstacle avoidance route planning method, vehicle obstacle avoidance method, computer readable storage medium and AGV car Download PDF

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Publication number
CN112232201A
CN112232201A CN202011105119.7A CN202011105119A CN112232201A CN 112232201 A CN112232201 A CN 112232201A CN 202011105119 A CN202011105119 A CN 202011105119A CN 112232201 A CN112232201 A CN 112232201A
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vehicle
obstacle avoidance
obstacle
route
point cloud
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傅峰峰
江志强
林麟琪
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Guangzhou Fugang Life Intelligent Technology Co Ltd
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Guangzhou Fugang Wanjia Intelligent Technology Co Ltd
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Publication of CN112232201A publication Critical patent/CN112232201A/en
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • 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
    • G05D1/20—Control system inputs
    • G05D1/24—Arrangements for determining position or orientation
    • G05D1/242—Means based on the reflection of waves generated by the vehicle
    • 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
    • G05D1/20—Control system inputs
    • G05D1/24—Arrangements for determining position or orientation
    • G05D1/243—Means capturing signals occurring naturally from the environment, e.g. ambient optical, acoustic, gravitational or magnetic signals
    • G05D1/2435—Extracting 3D information
    • 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
    • G05D1/60—Intended control result
    • G05D1/617—Safety or protection, e.g. defining protection zones around obstacles or avoiding hazards
    • G05D1/622—Obstacle avoidance
    • 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
    • G05D1/60—Intended control result
    • G05D1/644—Optimisation of travel parameters, e.g. of energy consumption, journey time or distance
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional objects
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2105/00—Specific applications of the controlled vehicles
    • G05D2105/20—Specific applications of the controlled vehicles for transportation
    • G05D2105/28—Specific applications of the controlled vehicles for transportation of freight
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2107/00—Specific environments of the controlled vehicles
    • G05D2107/70—Industrial sites, e.g. warehouses or factories
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2109/00—Types of controlled vehicles
    • G05D2109/10—Land vehicles
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2111/00—Details of signals used for control of position, course, altitude or attitude of land, water, air or space vehicles
    • G05D2111/10—Optical signals
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2111/00—Details of signals used for control of position, course, altitude or attitude of land, water, air or space vehicles
    • G05D2111/10—Optical signals
    • G05D2111/17—Coherent light, e.g. laser signals
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2111/00—Details of signals used for control of position, course, altitude or attitude of land, water, air or space vehicles
    • G05D2111/60—Combination of two or more signals
    • G05D2111/67—Sensor fusion

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

The invention provides a vehicle obstacle avoidance route planning method, a vehicle obstacle avoidance method, a computer readable storage medium and an AGV, wherein the vehicle obstacle avoidance route planning method comprises the following steps: scanning to obtain a horizontal two-dimensional point cloud image in a certain area range in front of the vehicle; shooting to obtain a three-dimensional image with depth of field in the height range from the ground to the height not lower than the height of the vehicle body in front of the vehicle; mapping the three-dimensional image to the horizontal two-dimensional point cloud image to form a new horizontal two-dimensional point cloud image; and if the new horizontal two-dimensional point cloud image has the obstacle, planning an obstacle avoidance route for avoiding the obstacle on the new horizontal two-dimensional point cloud image. The method solves the problem that the AGV cannot avoid the obstacle due to the fact that the obstacle in front of the AGV is lower than the top end of the vehicle body but higher than the radar scanning horizontal plane and cannot be scanned by the radar. Compared with a method for avoiding obstacles by using a fisheye camera or a three-dimensional radar, the method has the advantages of less calculated amount and good real-time performance.

Description

Vehicle obstacle avoidance route planning method, vehicle obstacle avoidance method, computer readable storage medium and AGV
Technical Field
The invention relates to the technical field of AGV trolleys, in particular to a vehicle obstacle avoidance route planning method, a vehicle obstacle avoidance method, a computer readable storage medium and an AGV trolley.
Background
The existing AGV trolley is in the process of advancing, the obstacle is usually scanned and avoided by utilizing a radar, the radar is usually horizontally and fixedly installed at the front end of the AGV trolley, a scanning area is formed by the radar in the horizontal area in front of the AGV trolley, and a horizontal two-dimensional point cloud image with the obstacle can be formed if the obstacle is located in the scanning area, so that the obstacle in a certain range on the horizontal direction of the height where the radar is located before the scanning trolley can be scanned. However, if the obstacle in the front of the vehicle is located at a height below the top of the vehicle body but above the radar scan level, the obstacle will block the travel of the AGV but will not be scanned by the radar, possibly causing the AGV to hit the obstacle. In addition, in the prior art, a three-dimensional radar is adopted for scanning to obtain a three-dimensional point cloud image, or a fisheye camera is adopted for obtaining a three-dimensional image to plan an obstacle avoidance route. However, both methods have the disadvantages of large calculation amount and poor real-time performance.
Disclosure of Invention
The invention aims to solve the technical problems of how to enable a vehicle to smoothly avoid an obstacle which is lower than the top end of a vehicle body but higher than a radar scanning plane, and avoid the problems of huge calculation amount and poor real-time performance caused by the adoption of a fisheye camera or a three-dimensional radar.
In order to solve the technical problem, the invention provides a vehicle obstacle avoidance route planning method, which comprises the following steps:
A. scanning to obtain a horizontal two-dimensional point cloud image in a certain area range in front of the vehicle;
the method is characterized by further comprising the following steps:
B. shooting to obtain a three-dimensional image with depth of field in the height range from the ground to the height not lower than the height of the vehicle body in front of the vehicle;
C. mapping the three-dimensional image to the horizontal two-dimensional point cloud image to form a new horizontal two-dimensional point cloud image;
D. if an obstacle exists on the new horizontal two-dimensional point cloud image, an obstacle avoiding route avoiding the obstacle is planned on the new horizontal two-dimensional point cloud image.
Preferably, a step p performed before said step a is included planning an initial route for said vehicle to travel from an initial position to a target position; and D, planning at least two traveling routes capable of avoiding the obstacle, and selecting the route with the minimum deviation degree compared with the initial route as the obstacle avoiding route.
Preferably, in the step D, after at least two travel routes capable of avoiding the obstacle are planned, a distance difference between the initial route and each travel route is calculated, and the deviation degree is determined according to the distance difference.
Preferably, the smaller the course difference, the smaller the deviation of the corresponding travel route.
Preferably, in the step B, after the three-dimensional image is obtained by shooting, a preset height is selected from the three-dimensional image, a part of the three-dimensional image not higher than the preset height is used as a ground, and a part of the three-dimensional image not higher than the preset height is removed.
Preferably, in the step a, a radar is used for scanning to obtain a horizontal two-dimensional point cloud image in a certain area range in front of the vehicle; in the step B, the preset height is a height at which the radar is located.
The invention also provides a vehicle obstacle avoidance method which is characterized in that the vehicle obstacle avoidance route planning method is executed to obtain the obstacle avoidance route, and the vehicle is enabled to travel according to the obstacle avoidance route to avoid the obstacle.
The present invention also provides a computer readable storage medium having stored thereon a computer program which, when being executed by a processor, implements the steps of the vehicle obstacle avoidance route planning method or the steps of the vehicle obstacle avoidance method.
The invention also provides an AGV comprising a vehicle body, a radar, a depth camera and a control device, wherein the radar and the depth camera are arranged on the vehicle body, the control device is respectively and electrically connected with the radar and the depth camera, the control device comprises a computer readable storage medium and a processor which are mutually connected, and the computer readable storage medium is as above; the step A is to obtain a horizontal two-dimensional point cloud image in a certain area range in front of the vehicle by utilizing the radar scanning; and the upper limit of the visual angle of the depth camera is not lower than the top end of the vehicle body, and the step B is to obtain a three-dimensional image with depth of field in the height range, wherein the front of the vehicle is not lower than the height of the vehicle body, by utilizing the depth camera.
Preferably, the radar is mounted on the vehicle body, in particular horizontally at the front end of the vehicle body, and the depth camera is mounted on the vehicle body, in particular horizontally at the top of the vehicle body.
The invention has the following beneficial effects: because the height range of the shot three-dimensional image of the front of the vehicle is from the ground to not lower than the height of the vehicle body, even if the obstacle which is lower than the top end of the vehicle body but not lower than the radar exists in the front of the vehicle, the obstacle does not exist in the scanned horizontal two-dimensional point cloud image, and the obstacle also exists in the shot three-dimensional image, therefore, after the three-dimensional image is mapped to the horizontal two-dimensional point cloud image to form a new horizontal two-dimensional point cloud image, the obstacle exists in the new two-dimensional point cloud image, and after an obstacle avoidance route which avoids the obstacle is planned on the new horizontal two-dimensional point cloud image, the vehicle can automatically avoid the obstacle which is lower than the top end of the vehicle body but not lower than the radar when the vehicle moves along the obstacle avoidance route. In addition, compared with a method adopting a fisheye camera or a three-dimensional radar obstacle avoidance method, the method has the advantages of being small in calculation amount and good in real-time performance.
Drawings
FIG. 1 is a schematic view of an AGV cart in a travel state.
Description of reference numerals: 1-a vehicle body; 2-radar; 3-a depth camera; 4-obstacle.
Detailed Description
As shown in fig. 1, the AGV includes a vehicle body 1, a radar 2, a depth camera 3, and a control device (not shown), wherein: the radar 2 is a laser radar which is horizontally and fixedly arranged at the front end of the vehicle body 1, and the radar 2 forms a scanning area in a horizontal area in front of the vehicle body 1 so as to obtain a horizontal two-dimensional point cloud image; the depth camera 3 is horizontally and fixedly arranged on the top of the vehicle body 1 and is positioned above the radar 2, and the upper limit of the visual angle of the depth camera 3 is not lower than the top end of the vehicle body 1, so that a three-dimensional image with depth of field in the height range from the ground to the height of the vehicle body 1 can be shot and obtained; the control device is respectively and electrically connected with the radar 2 and the depth camera 3.
Before the AGV car travels from the initial position to the target position, the control device plans an initial route for the vehicle to travel from the initial position to the target position. The control device controls the AGV to travel according to an initial route, in the traveling process, a barrier 4 which is lower than the top end of the vehicle body 1 and higher than the radar 2 exists on the initial route, then the control device plans a vehicle obstacle avoidance route which enables the AGV to avoid the barrier 4, and the specific planning process comprises the following steps A-D:
step A: and scanning by using a radar 2 to obtain a horizontal two-dimensional point cloud image in a scanning area in front of the vehicle.
And B: the method comprises the steps of shooting a three-dimensional image with depth of field in the height range from the ground to the height not lower than the height of a vehicle body 1 in front of the vehicle by using a depth camera 3, selecting the height of a radar 2 as a preset height after the three-dimensional image is shot, taking the part of the three-dimensional image not higher than the preset height as the ground, and removing the part of the three-dimensional image not higher than the preset height, so that the ground does not exist in the part of the three-dimensional image removed, and the ground is prevented from being used as an obstacle.
And C: and mapping the three-dimensional image with the ground part removed into a horizontal two-dimensional point cloud image to form a new horizontal two-dimensional point cloud image. The obstacle 4 located on the initial route appears in the three-dimensional image, so that in the process of mapping the three-dimensional image to the horizontal two-dimensional point cloud image, the obstacle 4 is also mapped to the horizontal two-dimensional point cloud image, namely the obstacle 4 exists in the new horizontal two-dimensional point cloud image.
Step D: when the obstacle 4 exists in the new horizontal two-dimensional point cloud image, the control device plans a first travel route for turning the AGV left to avoid the obstacle 4 and then travel to the target position, plans a second travel route for turning the AGV right to avoid the obstacle 4 and then travel to the target position, calculates a first distance difference between the initial route and the first travel route, specifically, the first travel route is longer than the initial route by one meter, calculates a second distance difference between the initial route and the second travel route, specifically, the second travel route is longer than the initial route by two meters, and the two distance differences respectively reflect the deviation degrees of the two travel routes, wherein the smaller the distance difference is, the smaller the deviation degree of the corresponding travel route is, so the deviation degree of the first travel route is the smallest, the control device selects the first travel route as an obstacle avoidance route.
After the control device obtains the obstacle avoidance route through planning, the related circuit is controlled to enable the AGV to move according to the obstacle avoidance route instead, and then the AGV can avoid the obstacle 4 and then move to the target position. Because the height range of the front three-dimensional image shot by the depth camera 3 is from the ground to the position not lower than the height of the vehicle body 1, the obstacle 4 is higher than the radar 2 even if the height of the obstacle 4 is higher than the radar 2, so that the obstacle 4 does not exist in the horizontal two-dimensional point cloud image obtained by scanning of the radar 2, and the obstacle 4 also exists in the three-dimensional image shot by the depth camera 3, therefore, the three-dimensional image is mapped onto the horizontal two-dimensional point cloud image to form a new horizontal two-dimensional point cloud image, and after an obstacle avoiding route avoiding the obstacle 4 is planned on the new horizontal two-dimensional point cloud image, the AGV trolley is enabled to travel according to the obstacle avoiding route, and the obstacle 4 higher than the radar 2 can be automatically avoided.
The control device comprises a computer readable storage medium and a processor which are connected with each other, wherein a computer program is stored in the computer readable storage medium, and when the computer program is executed by the processor, the vehicle obstacle avoidance route planning method and/or the vehicle obstacle avoidance method are/is realized, and the intelligent obstacle avoidance and the travel of the AGV trolley are controlled.
In the methods set forth directly or indirectly in the specification, various steps and operations are described in one possible order of operation, but those skilled in the art will recognize that steps and operations may be rearranged, substituted, or eliminated without necessarily departing from the spirit and scope of the invention. It is understood that the examples and embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Various modifications or alterations in view thereof will be suggested to those skilled in the art and are intended to be included within the scope of the claims of this application.

Claims (10)

1.一种车辆避障路线规划方法，包括如下步骤：1. A vehicle obstacle avoidance route planning method, comprising the following steps: A.扫描得到车前一定区域范围内的水平二维点云图像；A. Scanning to obtain a horizontal two-dimensional point cloud image within a certain area in front of the car; 其特征是，还包括如下步骤：It is characterized in that it also includes the following steps: B.拍摄得到车前从地面到不低于车体高度的高度范围内具有景深的三维图像；B. Take a three-dimensional image with depth of field in front of the car from the ground to a height not lower than the height of the car body; C.将所述三维图像映射到所述水平二维点云图像中，形成新的水平二维点云图像；C. the three-dimensional image is mapped to the horizontal two-dimensional point cloud image to form a new horizontal two-dimensional point cloud image; D.若所述新的水平二维点云图像上存在障碍物，则在所述新的水平二维点云图像上规划出避开所述障碍物的避障路线。D. If there is an obstacle on the new horizontal two-dimensional point cloud image, plan an obstacle avoidance route avoiding the obstacle on the new horizontal two-dimensional point cloud image. 2.根据权利要求1所述的车辆避障路线规划方法，其特征是：2. vehicle obstacle avoidance route planning method according to claim 1 is characterized in that: 包括在所述步骤A之前执行的步骤P.规划所述车辆从初始位置行进到目标位置的初始路线；Including step P. planning the initial route of the vehicle from the initial position to the target position performed before the step A; 在所述步骤D中，规划出至少两条能避开所述障碍物的行进路线，从中选取与所述初始路线相比偏离度最小者作为所述避障路线。In the step D, at least two travel routes that can avoid the obstacle are planned, and the route with the smallest deviation compared with the initial route is selected as the obstacle avoidance route. 3.根据权利要求2所述的车辆避障路线规划方法，其特征是，在所述步骤D中，在规划出至少两条能避开所述障碍物的行进路线之后，计算所述初始路线与各条行进路线之间的路程差值，根据所述路程差值确定所述偏离度。3 . The method for planning a vehicle obstacle avoidance route according to claim 2 , wherein in the step D, after planning at least two travel routes that can avoid the obstacle, the initial route is calculated. 4 . and the distance difference between each travel route, and the deviation is determined according to the distance difference. 4.根据权利要求3所述的车辆避障路线规划方法，其特征是，所述路程差值越小，对应的行进路线的所述偏离度越小。4 . The method for planning a vehicle obstacle avoidance route according to claim 3 , wherein the smaller the distance difference is, the smaller the deviation degree of the corresponding travel route is. 5 . 5.根据权利要求1所述的车辆避障路线规划方法，其特征是，在所述步骤B中，拍摄得到所述三维图像之后，在所述三维图像中选取一预设高度，将不高于所述预设高度的三维图像的部分作为地面，去除不高于所述预设高度的所述三维图像的部分。5 . The method for planning a vehicle obstacle avoidance route according to claim 1 , wherein in the step B, after the three-dimensional image is obtained by shooting, a preset height is selected in the three-dimensional image, and the height is not high. 6 . The part of the three-dimensional image at the preset height is used as the ground, and the part of the three-dimensional image not higher than the preset height is removed. 6.根据权利要求5所述的车辆避障路线规划方法，其特征是：在所述步骤A中，利用雷达扫描得到车前一定区域范围内的水平二维点云图像；在所述步骤B中，所述预设高度是所述雷达所处的高度。6. The vehicle obstacle avoidance route planning method according to claim 5, wherein in the step A, a horizontal two-dimensional point cloud image within a certain area in front of the vehicle is obtained by using radar scanning; in the step B , the preset height is the height at which the radar is located. 7.一种车辆避障方法，其特征是，执行权利要求1至6任一项所述的车辆避障路线规划方法，得到所述避障路线，令所述车辆改为按照所述避障路线行进以避开所述障碍物。7. A vehicle obstacle avoidance method, characterized in that the method for planning a vehicle obstacle avoidance route according to any one of claims 1 to 6 is executed, the obstacle avoidance route is obtained, and the vehicle is changed to follow the obstacle avoidance route. Route travel to avoid the obstacles. 8.一种计算机可读存储介质，其上存储有计算机程序，其特征是，所述计算机程序被处理器执行时实现权利要求1至6任一项所述的车辆避障路线规划方法中的步骤或权利要求7所述的车辆避障方法中的步骤。8. A computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the method in the vehicle obstacle avoidance route planning method according to any one of claims 1 to 6 is realized. steps or steps in the vehicle obstacle avoidance method of claim 7 . 9.一种AGV小车，包括车体、雷达、深度摄像头和控制装置，所述雷达和所述深度摄像头安装在所述车体上，所述控制装置分别电连接所述雷达和所述深度摄像头，所述控制装置包括相互连接的计算机可读存储介质和处理器，其特征是：所述计算机可读存储介质如权利要求8所述；所述步骤A具体是利用所述雷达扫描得到车前一定区域范围内的水平二维点云图像；所述深度摄像头的视角上限不低于所述车体顶端，所述步骤B具体是利用所述深度摄像头拍摄得到车前不低于车体高度的高度范围内具有景深的三维图像。9. An AGV car, comprising a vehicle body, a radar, a depth camera and a control device, the radar and the depth camera are mounted on the vehicle body, and the control device is electrically connected to the radar and the depth camera respectively , the control device comprises a computer-readable storage medium and a processor which are connected to each other, and is characterized in that: the computer-readable storage medium is as described in claim 8; A horizontal two-dimensional point cloud image within a certain area; the upper limit of the angle of view of the depth camera is not lower than the top of the vehicle body, and the step B is specifically to use the depth camera to capture the front of the vehicle and not lower than the height of the vehicle body. 3D image with depth of field in height range. 10.根据权利要求9所述的AGV小车，其特征是，所述雷达安装在所述车体上具体是水平地安装在所述车体前端，所述深度摄像头安装在所述车体上具体是水平地安装在所述车体顶部。10 . The AGV car according to claim 9 , wherein the radar is installed on the vehicle body, specifically, is horizontally installed at the front end of the vehicle body, and the depth camera is installed on the vehicle body. 10 . is installed horizontally on the top of the vehicle body.
CN202011105119.7A 2020-10-15 2020-10-15 Vehicle obstacle avoidance route planning method, vehicle obstacle avoidance method, computer readable storage medium and AGV car Pending CN112232201A (en)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115170797A (en) * 2022-06-01 2022-10-11 杭州海康机器人技术有限公司 Control method and device for mobile robot
WO2022227877A1 (en) * 2021-04-27 2022-11-03 北京石头创新科技有限公司 Obstacle avoidance method and apparatus for automatic walking device, medium, and electronic device

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180107226A1 (en) * 2016-10-17 2018-04-19 Mediatek Inc. Path planning method and related navigation device
CN108663681A (en) * 2018-05-16 2018-10-16 华南理工大学 Mobile Robotics Navigation method based on binocular camera Yu two-dimensional laser radar
CN109658373A (en) * 2017-10-10 2019-04-19 中兴通讯股份有限公司 A kind of method for inspecting, equipment and computer readable storage medium
CN110286387A (en) * 2019-06-25 2019-09-27 深兰科技（上海）有限公司 Obstacle detection method, device and storage medium applied to automatic driving system
CN110979321A (en) * 2019-12-30 2020-04-10 北京深测科技有限公司 Obstacle avoidance method for unmanned vehicle

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180107226A1 (en) * 2016-10-17 2018-04-19 Mediatek Inc. Path planning method and related navigation device
CN109658373A (en) * 2017-10-10 2019-04-19 中兴通讯股份有限公司 A kind of method for inspecting, equipment and computer readable storage medium
CN108663681A (en) * 2018-05-16 2018-10-16 华南理工大学 Mobile Robotics Navigation method based on binocular camera Yu two-dimensional laser radar
CN110286387A (en) * 2019-06-25 2019-09-27 深兰科技（上海）有限公司 Obstacle detection method, device and storage medium applied to automatic driving system
CN110979321A (en) * 2019-12-30 2020-04-10 北京深测科技有限公司 Obstacle avoidance method for unmanned vehicle

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022227877A1 (en) * 2021-04-27 2022-11-03 北京石头创新科技有限公司 Obstacle avoidance method and apparatus for automatic walking device, medium, and electronic device
US12535832B2 (en) 2021-04-27 2026-01-27 Beijing Roborock Innovation Technology Co., Ltd. Obstacle avoidance method for self-propelled device, medium, and self-propelled device
CN115170797A (en) * 2022-06-01 2022-10-11 杭州海康机器人技术有限公司 Control method and device for mobile robot

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