Biped Robot Footstep Planning with Global-Path-Guided Node Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing path planning algorithms for wheeled robots, such as the A* search algorithm, are inefficient for biped robots due to the increased search range and calculation complexity when planning foot placements, which restricts their performance, especially in scenarios requiring high real-time navigation.
Innovation Solution
A biped robot path planning method that combines the robot's parameters and real-time motion information to reduce the number of nodes to be searched, using a priority queue and cost evaluation function to optimize foot placement selection, and incorporates a global path to guide the search and reduce candidate nodes, thereby improving search efficiency and planning speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing wheeled robot path planning algorithms (e.g., A* search algorithm) are applied to biped robots, then the robot can achieve navigation functionality, but the search range and calculation complexity increase significantly, reducing real-time performance
Solution Approach 1:
The patent divides the path planning problem into two independent stages: global path planning (centroid-level routing) and local foot placement planning (leg-level execution). This segmentation allows each stage to use optimized algorithms appropriate to its scale, reducing overall computational complexity while maintaining complete navigation functionality.
Solution Approach 2:
The patent introduces a dual-level planning dimension: the global planner operates in the centroid configuration space while the local planner operates in the foot placement configuration space. This dimensional separation enables independent optimization of each planning layer, improving real-time performance without sacrificing adaptability.
2Manufacturing precision
If the search range is expanded to cover all possible foot placements for biped robots, then complete path coverage is achieved, but the calculation complexity and search time increase dramatically
Solution Approach 1:
The global path planner performs preliminary routing at the centroid level before local foot placement planning begins. This preliminary action constrains the subsequent local search to only those areas relevant to the global path, dramatically reducing calculation complexity while maintaining complete path coverage and planning accuracy.
Solution Approach 2:
The patent applies different planning strategies to different spatial scales: global-level A* search for centroid routing and local-level constrained optimization for foot placements. This local quality approach ensures high planning accuracy at each scale while minimizing overall computational complexity through targeted search refinement.
Data Source
AI summary
A path planning method and a biped robot using the same are provided. The method includes: generating a candidate node set for a next foot placement based on a biped robot's own parameters and joint information of a current node, adding valid candidate nodes in the candidate node set to a priority queue so as to select optimal nodes for realizing next node expansion. These optimal nodes are output to generate a foot placement sequence from an initial node to a target node, which can greatly reduce the search amount for path nodes when the robot's legs intersect and touch the ground, thereby improving the efficiency of path planning.