Bidirectional Path Planning for Faster Collision-Free Robot Motion
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Solution Overview
Problem
Current path planning algorithms for industrial moving objects, such as mechanical arms and robots, are inefficient as they take a long time to construct a collision-free path, failing to meet the requirements of rapid and optimized path planning.
Innovation Solution
A path planning method that involves constructing two exploration trees from the starting and end positions of a moving object, growing them towards each other while considering obstacle information, and connecting them when the distance between tree nodes is within a preset step length, utilizing a combination of random and targeted learning to balance growth and avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sampling-based planning algorithms (RRT) are used for path planning, then the algorithm exhibits strong randomness and can find collision-free paths, but it takes a long time to construct the path and does not meet current path planning requirements
Solution Approach 1:
The path planning process is segmented into two independent exploration trees: a first exploration tree growing from the starting position and a second exploration tree growing from the end position. Each tree independently explores the configuration space toward the other, allowing parallel computation and reducing overall planning time while maintaining collision-free path finding through separate obstacle avoidance checks for each tree
Solution Approach 2:
The algorithm inverts the traditional single-tree growth approach by having two trees grow simultaneously from opposite ends (start and goal positions) toward each other. This bidirectional growth strategy reduces the search space each tree must cover, thereby reducing computation time while maintaining the reliability of finding valid collision-free paths through the configuration space
Data Source
AI summary
Disclosed are a path planning method and apparatus, and a computer-readable storage medium. The path planning method may include: acquiring a motion space, a starting position, and an end position of a moving object, and information of an obstacle; constructing a first exploration tree starting from the starting position and constructing a second exploration tree starting from the end position in the motion space, the first exploration tree and the second exploration tree grow toward each other according to the information of the obstacle; and in response to a distance between a first tree node grown on the first exploration tree and a second tree node grown on the second exploration tree being not greater than a preset step length, connecting the first exploration tree and the second exploration tree to obtain a planned path of the moving object.