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Robot path planning method and system

A technology of path planning and robotics, applied to instruments, road network navigators, navigation, etc., can solve the problems of small application range and inapplicability to complex and high dynamic scenes, and achieve wide application range, improve efficiency, versatility, and high efficiency Effect

Inactive Publication Date: 2020-06-16
杭州指数星空智能科技有限责任公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] The present invention mainly solves the problem that the prior art is not suitable for complex and high-dynamic scenes and has a small application range, and provides a robot path planning method and system with high versatility and capable of realizing robot path planning in high-dynamic and complex scenes

Method used

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  • Robot path planning method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0048] A robot path planning method, such as figure 1 Shown: Include the following steps:

[0049] S1: Use visual sensors to obtain environmental information in the robot running scene; when using visual sensors to obtain environmental information, use SFM (Structure from Motion, motion recovery structure) or visual SLAM (Simultaneous Localization and Mapping, simultaneous positioning and mapping) to obtain Environmental information based on visual landmark point cloud description. SFM is implemented through the development package openMVG, and visual SLAM is implemented through ORB-SLAM2 proposed by Raul Mur-Artal et al.;

[0050] S2: Convert the environmental information into a global grid map. The smaller the grid, the more accurate the trajectory of the robot based on the planning and processing of the global grid map. In this embodiment, the size of each grid is set to 5cm;

[0051] S3: Use the perception device to sense and obtain the dynamic target object in the runni...

Embodiment 2

[0071] The difference between this embodiment and Embodiment 1 is that this embodiment uses a laser radar sensor to obtain robot operation scene information.

Embodiment 3

[0073] The difference between this embodiment and Embodiment 1 is that this embodiment uses the D* algorithm to calculate the global path of the subgraph.

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Abstract

The invention relates to a robot path planning method and system. The method comprises the following steps: acquiring environmental information in a robot operation scene; converting the environment information into a global grid map; sensing and acquiring a dynamic target object in a running scene by using sensing equipment, and updating the position of the dynamic target object in the global grid map at a specific frequency; dividing the global grid map into a plurality of sub-graphs, calculating the sub-graphs to be passed through, and obtaining sub-graph global paths of the sub-graphs at acertain frequency; and calculating a local path from the current position of the robot to the sub-graph global path end point of the sub-graph where the current robot is located at a certain frequency. The system for realizing the method comprises a sensing module, a wireless communication module, a cloud robot scheduling module and a robot body module. The method and the system have the advantages that the path planning efficiency in a complex high-dynamic scene is high; the trap problem in a complex scene is solved, and the efficiency and universality of a path planning algorithm are improved; the application range is wide.

Description

technical field [0001] The invention relates to the field of robot path planning, in particular to a robot path planning method and system. Background technique [0002] When the robot has global environmental information, one-time global planning can be used to obtain a safe and passable path from the start point to the end point, and can be optimized for certain indicators. Since the path planning problem is a classic NP-hand problem, traditional path planning algorithms have different problems: such as the computational efficiency of the enumeration and random search methods is too low, and the gradient method is easy to fall into a local minimum. In recent years, academia and industry have proposed to use improved genetic algorithm, neural network algorithm, random tree and other methods to plan the robot's path planning algorithm, but these methods have the problems of large search space, complex algorithm and low efficiency. [0003] The method disclosed by CN10309220...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/34
CPCG01C21/343G01C21/3446
Inventor 陈水弟
Owner 杭州指数星空智能科技有限责任公司
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