Multi-Arm Motion Planning With Dynamic Roadmaps for Collision Avoidance
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Solution Overview
Problem
Existing methods for collision-free motion planning in multi-arm robots are inefficient, particularly in dynamically changing environments, as they often rely on probabilistic methods that generate non-deterministic trajectories and require unpredictable computing times, or local optimization methods that struggle in complex environments.
Innovation Solution
The method employs dynamic roadmaps for each manipulator, pre-calculating mappings between working spaces and configuration spaces to enable fast, deterministic re-planning by coordinating motion paths independently and efficiently, allowing for rapid collision checks and flexible extension to multi-arm systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If probabilistic planning methods are used for multi-arm robot motion planning, then the planning can be performed in complex environments, but the trajectories generated are non-deterministic and the computing time is unpredictable
Solution Approach 1:
The patent pre-calculates dynamic roadmaps and mappings between working spaces and configuration spaces before actual motion planning is needed. This preliminary action stores pre-computed path information that can be quickly retrieved and coordinated during real-time operation, eliminating the need for probabilistic search during execution and providing deterministic trajectories with predictable computing times.
2Adaptability or versatility
If probabilistic planning methods are used for multi-arm robot motion planning, then the planning can be performed in complex environments, but the computing time required is generally not predictable
Solution Approach 1:
The patent pre-calculates dynamic roadmaps and mappings between working spaces and configuration spaces before actual motion planning is needed. This preliminary action stores pre-computed path information that can be quickly retrieved and coordinated during real-time operation, eliminating the need for probabilistic search during execution and providing deterministic trajectories with predictable computing times.
3Productivity
If local optimization methods are used for motion planning, then the computation is faster, but solutions cannot be found in complex environments
Solution Approach 1:
The patent pre-calculates dynamic roadmaps and mappings between working spaces and configuration spaces before actual motion planning is needed. This preliminary action stores pre-computed path information that can be quickly retrieved and coordinated during real-time operation, eliminating the need for probabilistic search during execution and providing deterministic trajectories with predictable computing times.
Solution Approach 2:
The patent introduces a coordination graph that operates in an extended configuration space combining both manipulators' degrees of freedom. This dimensional extension allows the system to solve complex coordination problems between multiple arms while maintaining computational efficiency through the pre-computed roadmaps, effectively adding a coordination dimension without proportionally increasing computation time.
4Reliability
If coupled approaches are used for motion planning of multi-arm robots, then coordination between arms is improved, but the computing complexity increases significantly
Solution Approach 1:
The patent pre-calculates dynamic roadmaps and mappings between working spaces and configuration spaces before actual motion planning is needed. This preliminary action stores pre-computed path information that can be quickly retrieved and coordinated during real-time operation, eliminating the need for probabilistic search during execution and providing deterministic trajectories with predictable computing times.
Solution Approach 2:
The patent divides the complex multi-arm planning problem into separate manipulator-specific dynamic roadmaps that are pre-computed independently. These segmented roadmaps are then coordinated through a coordination graph, allowing the system to maintain accurate coordination while reducing overall computational complexity by avoiding full coupled planning.
Data Source
AI summary
A method and corresponding apparatus for collision-free motion planning of a first manipulator in a first working space and a second manipulator in a second working space, wherein the first and second working spaces at least partially overlap. The method includes the steps of importing a first dynamic roadmap for a first configuration space of the first manipulator, wherein the first dynamic roadmap includes a first search graph and a first mapping between the first working space and the first search graph, and importing a second dynamic roadmap for a second configuration space of the second manipulator, wherein the second dynamic roadmap includes a second search graph and a second mapping between the second working space and the second search graph. Furthermore, the motion of the first manipulator and the second manipulator are coordinated based on the first dynamic roadmap and the second dynamic roadmap.