Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Mobile robot multistage obstacle avoidance system and method based on semantic laser

A technology for mobile robots and robot bodies, applied in control/adjustment systems, instruments, motor vehicles, etc., can solve the problems of inability to identify the type and characteristics of obstacles, reduced safety, and easy to cause safety problems.

Active Publication Date: 2021-05-28
SHANDONG ALESMART INTELLIGENT TECH CO LTD
View PDF12 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The mobile robot uses the above-mentioned single sensor or multi-sensor fusion traditional obstacle avoidance method to have excellent autonomous navigation performance in static scenes, but when the work scene is complex, the traditional method cannot identify the characteristics of the obstacle type. When the mobile robot estimates the obstacle pose and the actual obstacle pose, there is a large deviation, which can easily cause safety problems. At the same time, when the mobile robot is in the navigation state, it cannot make corresponding obstacle avoidance adjustments according to the obstacle characteristic information, resulting in the operation Reduced efficiency, reduced safety

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Mobile robot multistage obstacle avoidance system and method based on semantic laser
  • Mobile robot multistage obstacle avoidance system and method based on semantic laser
  • Mobile robot multistage obstacle avoidance system and method based on semantic laser

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0042] Such as figure 1 As shown, a semantic laser-based mobile robot multi-level obstacle avoidance system, the system includes multi-sensor fusion feature information extraction module, obstacle type recognition module, coupling information processing module and mobile robot motion planning module.

[0043] Such as Figure 2-3 As shown, this embodiment is combined with an autonomous guided vehicle (AGV). In the AGV, the multi-sensor fusion feature information extraction module of this embodiment includes two 2D laser radars, four monocular industrial cameras, and four ultrasonic sensor, figure 2 It shows the installation position of the components in the whole module.

[0044] Among them, the 2D lidar scans the obstacle information within 270° of the center of the circle where the radar is installed at high frequency, and returns the obstacle angle and distance point cloud coordinates based on its own coordinate system. The maximum distance of the obstacle is 5m.

[0045...

Embodiment 2

[0059] A multi-level obstacle avoidance method for a mobile robot based on semantic laser, which also combines this embodiment with an autonomous guided vehicle (AGV), as shown in Figure 6 As shown, it is the general flow chart of AGV 4 modules working together for multi-level obstacle avoidance. Figure 7 , 8 , 9, and 10 are its sub-processes, and the overall process includes the following steps:

[0060] According to the information obtained by the lidar on the robot body and the industrial camera, after coupling, the robot body can recognize the characteristic information of obstacles;

[0061] Divide the sector scanning range of the laser radar into three layers according to the distance between the obstacle and the robot body. The layer closest to the robot body is the dangerous range, the farthest layer is the safe range, and the rest is the deceleration range;

[0062] Determine whether the robot body is in the mapping state, and generate different obstacle avoidance...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a semantic laser-based mobile robot multistage obstacle avoidance system and method. The method comprises the steps: carrying out tight coupling on data of a laser radar, an industrial camera and an ultrasonic sensor to obtain semantic laser, so that a laser point cloud carries attitude information, obstacle types, motion ranges and other information; dividing the scanning range of the laser radar into three layers according to the distance between an obstacle and a robot body; judging whether the robot body is in a mapping state or not; and generating corresponding obstacle avoidance actions in the mapping state and the navigation state of the robot body according to the obstacle feature information. According to the invention, the unicity of traditional obstacle avoidance information is changed, so that the mobile robot has the ability of obstacle feature cognition in an unknown dynamic environment, and the flexibility of the whole obstacle avoidance system is improved.

Description

technical field [0001] The invention relates to the field of intelligent obstacle avoidance of mobile robots, in particular to a multi-level obstacle avoidance system and method for mobile robots based on semantic laser. Background technique [0002] Mobile robots are highly integrated devices that integrate mechanical substrates, drive systems, control systems, sensor detection systems, and job execution systems. Under the premise of rapid development of sensor technology, they are gradually becoming intelligent and mature, and have been widely used in industrial , logistics, service, medical and other fields. In different work scenarios, mobile robots need to complete real-time obstacle avoidance work to ensure environmental safety and their own safety. Obstacles are roughly divided into static obstacles and dynamic obstacles. Static obstacles include shelves, walls, Tables and chairs, etc., dynamic obstacles include people, equipment for large-scale space operations, ele...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/024G05D1/0242G05D1/0246G05D1/0255G05D1/0214G05D1/0221G05D1/0276
Inventor 周军宋凯吴迪皇攀凌周华章赵一凡高新彪杨子兵
Owner SHANDONG ALESMART INTELLIGENT TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com