Self-adaptive heuristic global path planning method and system for robot

A global path planning and self-adaptive technology, applied in instrumentation, surveying and navigation, comprehensive factory control, etc., can solve the problems of long planning path, low planning success rate, low effectiveness of complex obstacle maps, etc., to improve planning Excellent indicators of success rate and path length, and the effect of accurate path planning

Active Publication Date: 2022-07-05
湖南欣欣向荣智能科技有限公司
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Problems solved by technology

This paper belongs to the category of global path planning. The traditional global path planning method is a global path planning method based on sampling. This method cannot accurately calculate the distance between nodes and target points in the state space. High, low effectiveness on complex obstacle maps

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  • Self-adaptive heuristic global path planning method and system for robot
  • Self-adaptive heuristic global path planning method and system for robot
  • Self-adaptive heuristic global path planning method and system for robot

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Embodiment Construction

[0046] The graph theory description of the path planning problem is as follows: The input environment map for the path planning problem is a two-dimensional map, which can be expressed as: M=M 0 +M 1 , M 0 is the obstacle area, M 1 is the passable area, the state space M s Usually defined as M s =R n , n∈N, the starting point is x start ∈X, the target point is x goal ∈X, the set of sampling points X s ⊂X, where R n Represents the total set of spatial search states, each edge represents a state transition, n represents the number of map nodes, N represents the set of positive integers, and X represents the set of all nodes in the input map. Edges between sample points (nodes) can be defined as arbitrary nodes x p and x c The connections between are referred to as edges ( x p, x c ). where node x p is the parent node (closer to the starting point on the path), the node x c is a child node (closer to the destination point on the path). The forward search t...

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Abstract

The invention discloses a self-adaptive heuristic global path planning method and system for a robot. The method comprises the following steps: traversing an input environment map to obtain an initial state space, and carrying out collision point detection to obtain sampling points; aiming at the obtained sampling points, carrying out reverse search by starting from a target point to generate a reverse search point set, connecting the sampling points into edges and sorting the edges, and then constructing an adaptive heuristic function by utilizing child nodes of the ordered edges and the reverse search point set; and performing cost optimization based on an adaptive heuristic function, extending an ordered edge queue from a starting point to generate a forward search tree, extending the forward search tree to a target point to obtain a planned path, and repeating the steps for multiple times to obtain a final planned path. According to the method, rapid and accurate path planning can be realized, a relatively shortest path can be planned, and the planning success rate and the effectiveness on a complex obstacle map are improved.

Description

technical field [0001] The invention relates to a path planning technology in robot positioning and autonomous navigation, in particular to an adaptive heuristic global path planning method and system for robots. Background technique [0002] With the rapid development of robotics, simultaneous positioning and map construction are the basic key technologies in the robotics field. By fusing the information of lidar and depth camera, the advantages and disadvantages can be complemented, making up for the inevitable shortcomings of a single sensor, providing more accurate and robust environment map. On the basis of obtaining a two-dimensional or three-dimensional real-time map, the final realization of autonomous navigation of the robot requires the use of path planning technology. Path planning refers to automatically planning a path with the shortest length or the least cost between the starting point and the target point in a certain environment. The path planning method c...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20G01C21/00G06F16/901
CPCG01C21/20G01C21/005G06F16/9027Y02P90/02
Inventor 李树涛李松鞠孙斌
Owner 湖南欣欣向荣智能科技有限公司
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