Robot Look-Ahead Motion Planning for Shared Workspace Deadlocks
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Solution Overview
Problem
Existing motion planning techniques for robots in shared workspaces face challenges in efficiently generating collision-free paths, especially in dynamic environments, leading to reduced work throughput and increased computational time, particularly when multiple robots operate with high degrees of freedom and changing obstacles.
Innovation Solution
Implementing look-ahead motion planning that anticipates and assesses potential collisions by planning for multiple goals in advance, allowing for remedial actions such as generating new motion plans or adjusting the trajectory of other robots to prevent deadlocks, thereby ensuring efficient and collision-free operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If task-level de-confliction is used to ensure collision-free operation, then robot safety is improved, but work throughput decreases due to robots being idle for significant portions of time
Solution Approach 1:
The system performs look-ahead motion planning by determining motion plans for multiple successive goals before executing the current motion plan. This preliminary planning allows the robot to anticipate future collisions and adjust its trajectory in advance, enabling continuous operation without idle waiting time while maintaining collision-free operation.
2Productivity
If offline planning is used to achieve higher work throughput, then productivity improves, but computational time increases excessively for high degrees of freedom
Solution Approach 1:
The system segments the motion planning problem by determining motion plans for multiple successive goals incrementally rather than solving the entire high-DOF planning problem at once. This divides the computationally intensive offline planning into smaller, manageable segments that can be processed in real-time, reducing total computational time while maintaining high work throughput.
3Ease of operation
If conventional motion planning algorithms are used for high-DOF robots, then basic motion planning is achieved, but the planning becomes extremely time-consuming and infeasible for current architectures
Solution Approach 1:
The system performs preliminary motion planning for multiple successive goals before execution, allowing the robot to anticipate future collisions and adjust trajectories in advance. This look-ahead approach enables real-time collision detection and response without requiring extremely time-consuming comprehensive planning, making high-DOF robot operation feasible on current architectures.
Data Source
AI summary
The structures and algorithms described herein employ look ahead motion planning, in which motion planning for a least two goals is performed before a robot executes the resulting motion plans, and the ability to transition between the preceding one of the motion plans to a subsequent (e.g. following) one of the motions plans is assessed. Thus, the system can determine whether a robot will get trapped (e.g., blocked by another robot) at the end of a first motion plan, preventing, limiting or delaying execution of a second motion plan. Detection of such a condition can cause one or more remedial actions can be taken, for example generating a new, revised or replacement first motion plan. Other remedial action can moving another robot, performing motion planning for the other robot, to alleviate a blocking condition and/or determining a new order for the goals.