Shared-Workspace Robot Motion Planning for Collision-Free Scheduling
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Solution Overview
Problem
Coordination of multiple robots in a shared workspace is complex and inefficient, with existing methods struggling to optimize task execution and avoid collisions, leading to potential delays and increased energy consumption.
Innovation Solution
A scheduling system that generates and scores candidate motion plans for each robot based on 3D models of their motion paths, identifying potential collisions and optimizing task assignment to minimize interference and energy use, while allowing for flexible robot deployment and reduced scheduling time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple robots operate concurrently in a shared workspace, then productivity is improved, but the complexity of coordinating movements and avoiding collisions increases
Solution Approach 1:
The system segments the shared workspace into multiple workcells, each with its own robot. By dividing the large workspace into smaller zones, the coordination complexity is reduced while maintaining concurrent operation capability. Each workcell can be independently managed, making the overall system more tractable.
Solution Approach 2:
A centralized scheduling system acts as an intermediary between multiple robots, managing task assignments and motion planning. This mediator coordinates robot movements by generating and evaluating candidate motion plans, resolving conflicts before execution, and thereby reducing the direct coordination burden between robots.
2Reliability
If traditional motion planning methods are used for each robot independently, then individual robot task completion is achieved, but collisions and deadlocks occur between robots
Solution Approach 1:
The system merges individual robot motion planning into a unified multi-robot motion planning process. By combining the planning of multiple robots and evaluating their candidate motion plans together, the system identifies and resolves potential collisions and deadlocks before execution, ensuring safe concurrent operation.
Solution Approach 2:
The scheduling system performs preliminary action by generating and evaluating candidate motion plans for multiple robots before actual execution. This advance planning identifies potential conflicts and allows the system to select collision-free motion plans, preventing harmful interactions before they occur.
3Measurement precision
If human programmers manually coordinate robot movements, then precise control is achieved, but scheduling time becomes excessively long
Solution Approach 1:
The system implements self-service by automatically generating, evaluating, and selecting motion plans without human intervention. The scheduling system independently manages the complex coordination task, resolving conflicts and optimizing robot schedules algorithmically, which dramatically reduces scheduling time while maintaining precision through systematic evaluation of candidate plans.
4Object-affected harmful factors
If robots are positioned far apart in the workspace, then collisions are avoided, but the workspace requirements and system footprint increase
Solution Approach 1:
The centralized scheduling system acts as an intermediary that enables robots to operate closer together by mediating their movements. It generates coordinated motion plans that actively avoid collisions, allowing compact robot placement while maintaining safety through intelligent scheduling rather than physical separation.
Data Source
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AI summary
Methods, systems, and computer programs stored on computer storage devices, for coordinating movements of robots are disclosed. One of the methods includes, for each robot in a group of robots, identifying a set of tasks assigned to the robot and generating a plurality of candidate motion plans. The method further includes, for each candidate motion plan: (i) generating a 3D model that represents a volume of space through which the robot would move in executing the sequence of motions represented by the candidate motion plan, and (ii) determining a score for the candidate motion plan. The method further includes determining conflicts between candidate motion plans of different robots, selecting a motion plan from the candidate motion plans based on the score for the selected motion plan and the conflicts, and providing the selected motion plans for execution by the group of robots.