Disassembly-Based Robot Motion Planning for Tightly-Constrained Assembly
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Solution Overview
Problem
Existing robot motion planning techniques, such as RRT-based methods, are inefficient in handling complex geometries and planning assembly motions for tightly-constrained components, as they struggle to find precise path waypoints due to the need for precise collision-free evaluations in tightly-constrained regions.
Innovation Solution
A disassembly-based robot motion planning technique that starts at a tightly-constrained target configuration and uses a local search to generate nodes that extend a path toward a loosely-constrained initial configuration, reducing the number of unproductive configurations evaluated by proposing randomly-sampled waypoints and evaluating local samples for collision-free paths, thereby efficiently escaping the tightly-constrained region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If RRT-based methods are used for assembly motion planning, then the system can handle complex geometries, but the planning efficiency deteriorates due to the tightly-constrained target configuration requiring precise collision-free evaluations
Solution Approach 1:
The patent inverts the traditional assembly planning approach by starting the motion planning from the target configuration and working backward to the initial configuration, rather than planning forward from initial to target. This inversion allows the algorithm to escape the tightly-constrained region more efficiently by utilizing local search methods that can slide through constrained spaces, thereby improving planning efficiency while maintaining the ability to handle complex geometries
2Ease of operation
If RRT-based methods are used for assembly motion planning, then random exploration is performed, but the number of unproductive configurations evaluated increases due to the tightly-constrained target configuration
Solution Approach 1:
The patent applies preliminary action by performing a local search from the target configuration before committing to random exploration. The local search method预先 (in advance) identifies feasible paths through the tightly-constrained region, allowing the algorithm to avoid evaluating numerous unproductive configurations during subsequent random exploration phases
Solution Approach 2:
The patent introduces dynamics by switching between different planning strategies based on the current configuration state. When in tightly-constrained regions, the system uses local search with sliding operations; when in loosely-constrained regions, it uses random exploration. This dynamic adaptation reduces the number of unproductive evaluations by applying the appropriate method for each region type
3Productivity
If rule-based systems with geometric constraints are used, then planning efficiency improves, but the system can only handle simple part geometries
Solution Approach 1:
The patent segments the configuration space into tightly-constrained regions and loosely-constrained regions based on local geometry analysis. By dividing the planning problem into region-specific subproblems, the system can apply efficient local search methods in constrained regions while maintaining the ability to handle complex geometries throughout the entire assembly process
Data Source
AI summary
A robot motion planning technique for component assembly operations. Inputs to the motion planning technique include geometric models of the components being assembled, and initial and target configurations. The method begins at a tightly-constrained target or final configuration and plans in the direction of a loosely-constrained initial configuration. A randomly-sampled waypoint configuration is proposed, followed by a local search for feasible configurations which generates nodes that extend a path toward the initial configuration while sliding through the tightly-constrained region. The local search can be repeated multiple times for a given randomly-sampled configuration. When a completed path is found, the action sequence is trimmed to eliminate unnecessary extraneous motions in the loosely-constrained region. The disclosed method dramatically reduces the number of unproductive configurations evaluated and finds assembly solutions much faster in comparison to known tree-based motion planning methods.