Multi-Robot Deadlock Prevention via Trajectory Reservation
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Solution Overview
Problem
Existing systems fail to effectively prevent collisions between multiple robots in a manufacturing environment, particularly in three-dimensional space, and often result in costly downtime due to deadlocks when robots attempt to occupy the same workspace simultaneously.
Innovation Solution
A method for controlling motion interference that uses voxelized models to identify and avoid potential collision regions in real-time, allowing robots to execute deadlock-free motion statements and reserve trajectories without the need for I/O handshaking mechanisms, enabling three-dimensional collision detection and protection of critical process paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the wait and move process is used to prevent collisions, then collision prevention is improved, but working cycle time increases
Solution Approach 1:
The system performs preliminary actions by predicting future robot locations and reserving trajectories in advance before collisions occur. The trajectory reservation mechanism pre-establishes collision-free paths for multiple robots, eliminating the need for wait-and-move protocols during execution.
Solution Approach 2:
The system transitions from static interference space definitions to dynamic trajectory-based collision prevention. By continuously predicting robot positions and adjusting trajectory reservations in real-time, the system adapts to changing robot states and maintains collision-free operation without unnecessary waiting.
2Ease of manufacture
If static interference space checking is used, then implementation simplicity is improved, but collision prevention effectiveness deteriorates
Solution Approach 1:
The system adds the time dimension to traditional spatial interference checking by predicting future robot locations. Instead of checking only current positions, the system evaluates potential collisions along predicted trajectories, transforming a 3D spatial problem into a 4D spacetime problem that captures dynamic collision risks.
Solution Approach 2:
The system performs preliminary collision detection by predicting future robot positions before actual movement occurs. This advance prediction allows the system to identify and resolve potential collisions before they happen, improving prevention effectiveness while maintaining computational efficiency.
3Measurement precision
If element-by-element model comparison is performed in real-time, then collision detection accuracy is improved, but computational cost increases exponentially
Solution Approach 1:
The system extracts only the essential collision-related information from full robot models by working with simplified trajectory representations. Instead of comparing complete element-by-element models, the system focuses on predicted position data and trajectory intersections, dramatically reducing computational complexity while maintaining collision detection accuracy.
Solution Approach 2:
The system performs partial collision detection by focusing only on critical trajectory intersections rather than complete model comparisons. By applying collision detection selectively to predicted path intersections rather than all robot elements continuously, the system achieves sufficient accuracy with reduced computational overhead.
4Loss of information
If I/O handshaking mechanism is used for interference avoidance, then communication between controllers is improved, but system complexity and response time deteriorate
Solution Approach 1:
The system replaces mechanical I/O handshaking mechanisms with a software-based trajectory reservation and prediction system. Instead of using physical I/O signals and handshaking protocols between controllers, the system uses centralized trajectory management and prediction algorithms to coordinate robot movements, eliminating the need for complex I/O communication infrastructure.
Data Source
AI summary
A system and method for controlling avoiding collisions and deadlocks in a workcell containing multiple robots automatically determines the potential deadlock conditions and identifies a way to avoid these conditions. Deadlock conditions are eliminated by determining the deadlock-free motion statements prior to execution of the motions that have potential deadlock conditions. This determination of deadlock-free motion statements can be done offline, outside normal execution, or it can be done during normal production execution. If there is sufficient CPU processing time available, the determination during normal production execution provides the most flexibility to respond to dynamic conditions such as changes in I/O timing or the timing of external events or sequences. For minimal CPU impact the determination is done offline where many permutations of programming sequences can be analyzed and an optimized sequence of execution may be found.