Multi-Robot Path Coordination Under Sparse Networking
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Solution Overview
Problem
In environments like warehouses with limited or disrupted network connectivity, autonomous robotic devices may deviate from their scheduled paths, leading to potential collisions or operational errors due to the lack of continuous communication with a centralized control system.
Innovation Solution
A method where robotic devices receive time-parameterized paths and communicate with each other to adjust their execution based on their relative rates of progress, allowing them to modify their paths to synchronize and avoid collisions even in areas with weak communication links.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robotic devices operate with continuous central control, then coordination and collision avoidance are improved, but network connectivity requirements increase and system complexity increases
Solution Approach 1:
The system divides coordination functionality into two segments: centralized path planning (offloading complex computation to the central server) and decentralized execution (robots independently adjusting their paths using onboard processors). This segmentation reduces network dependency while maintaining coordination reliability.
Solution Approach 2:
The central control system pre-computes coordinated paths for multiple robotic devices before deployment. These pre-planned paths are then executed by the robots with minimal real-time communication, reducing the need for continuous network connectivity during operation.
2Reliability
If robotic devices communicate frequently to maintain synchronization, then collision avoidance is improved, but network bandwidth consumption increases and operation in sparse networking areas deteriorates
Solution Approach 1:
The system implements selective communication where robots only exchange information when necessary (e.g., when paths overlap or when one robot deviates from its planned path). This partial action approach maintains collision avoidance while reducing overall communication frequency and bandwidth consumption.
Solution Approach 2:
Each robotic device independently monitors its own path execution and autonomously adjusts its trajectory when deviations are detected or when it receives updates from other robots. This self-service capability reduces dependency on continuous central control and improves operation in sparse networking areas.
3Reliability
If robotic devices follow strict time-parameterized paths, then synchronization is improved, but adaptability to deviations and operational flexibility deteriorate
Solution Approach 1:
The path execution system is made dynamic by allowing robots to adjust their trajectories in real-time based on actual conditions. When a robot deviates from its time-parameterized path or when obstacles are detected, the system dynamically recomputes adjusted paths while maintaining overall synchronization, thus balancing reliability with adaptability.
Data Source
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AI summary
A method includes receiving a first time-parameterized path for the first robotic device, and an indication of a second robotic device having a second time-parameterized path that overlaps with the first time-parameterized path at a first location. The method also includes executing, by the first robotic device, a first portion of the first time-parameterized path before reaching the first location, wherein execution of the first portion corresponds to a first rate of progress of the first robotic device along the first time-parameterized path. The first robotic device then receives a communication signal from the second robotic device indicating a second rate of progress of the second robotic device along the second time- parameterized path. The method then includes the first robotic device determining a difference between the first rate of progress and the second rate of progress, and modifying execution of the first time-parameterized path based on the determined difference.