Elastic Robot Path Planning for Multi-Robot Collision Avoidance
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Solution Overview
Problem
Existing robotic systems face challenges in efficiently planning paths that avoid obstacles and collisions, especially in high-traffic environments where multiple robots interact, as current methods often require complex and computationally intensive calculations to account for the movements of all robots.
Innovation Solution
The implementation of an elastic path planning technique that uses force vectors to shape and deform candidate paths based on the swept regions of other robots, allowing the system to aggregate and adjust paths dynamically to avoid congested areas and ensure safe navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system uses traditional path planning methods to account for movements of all robots, then collision avoidance is achieved, but computational complexity increases significantly
Solution Approach 1:
The system segments the path planning problem by treating each robot's swept region as a separate entity. Instead of computing all possible interactions between robots simultaneously, the method divides the problem into individual robot path calculations, then aggregates their swept regions to identify conflict zones, significantly reducing computational complexity while maintaining collision avoidance reliability
Solution Approach 2:
The system introduces an intermediary representation called 'swept regions' that mediates between individual robot paths and collision detection. By calculating the swept regions of multiple robots and aggregating them, the system creates a simplified intermediate model that identifies high-traffic conflict zones without requiring complex real-time interaction calculations between all robot pairs
2Reliability
If the system plans paths for multiple robots in high-traffic environments, then navigation safety is improved, but path optimization efficiency decreases
Solution Approach 1:
The system performs preliminary calculations by determining the swept regions of multiple robots in advance before final path optimization. By pre-calculating where robots will be at different time steps and aggregating these regions to identify high-traffic zones beforehand, the system prepares optimization data that speeds up the final path planning while ensuring navigation safety through advance conflict zone identification
Solution Approach 2:
The system applies local quality by focusing computational effort on high-traffic regions identified through swept region aggregation. Instead of uniformly optimizing all path segments, the method concentrates optimization resources on areas where multiple robot paths overlap or conflict, improving navigation safety in critical zones while maintaining overall path optimization efficiency
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for planning a path of motion for a robot. In some implementations, a candidate path of movement is determined for each of multiple robots. A swept region, for each of the multiple robots, is determined that the robot would traverse through along its candidate path. At least some of the swept regions for the multiple robots is aggregated to determine amounts of overlap among the swept regions at different locations. Force vectors directed outward from the swept regions are assigned, wherein the force vectors have different magnitudes assigned according to the respective amounts of overlap of the swept regions at the different locations. A path for a particular robot to travel is determined based on the swept regions and the assigned magnitudes of the forces.