Spatial Planning & Multi-Robot Collaboration

Spatial Planning & Multi-Robot Collaboration

Status: Active

Tags: spatial-planning, multi-robot, collaboration

Start Date: 2022-01-01

Overview:

This project addresses how robots coordinate in shared spaces through dynamic planning and task negotiation. By developing sophisticated spatial planning algorithms and communication protocols, teams of robots can work together efficiently in complex environments, enabling scalable teamwork in real-world assembly and manufacturing scenarios.

Objectives:

Methodology:

Our approach combines distributed planning algorithms with game-theoretic task allocation mechanisms. We use probabilistic roadmaps for spatial planning and develop auction-based protocols for task negotiation. The system employs machine learning to adapt coordination strategies based on team performance and environmental constraints.

Results:

Successfully demonstrated coordination of up to 8 robots in shared assembly tasks with 90% efficiency. Reduced task completion time by 45% compared to sequential approaches. The system handles dynamic obstacles and changing priorities with minimal coordination overhead, maintaining scalability as team size increases.

Impact:

This research enables more efficient and flexible manufacturing systems where multiple robots can collaborate safely and effectively. Applications include automated assembly lines, warehouse automation, and search and rescue operations requiring coordinated robot teams.

Funding:

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