Velocity Potential Field Modulation for Dense Coordination of Polytopic Swarms and Its Application to Assistive Robotic Furniture
Lixuan Tang, David Rüegg, Runze Zhang, Anastasia Bolotnikova, Jan M. Rabaey, Auke Ijspeert
AI summary
Problem
Coordinating dense swarms of robots with complex shapes in confined indoor spaces often leads to collisions, oscillations, and deadlocks due to inadequate handling of neighbor interactions and target convergence.
Approach
VPFM modulates each robot's attractive velocity to flow around neighbors using normal compression and tangent stretching, while dynamically scaling down repulsion strength and range as robots near their targets to maintain reactivity.
Key results
- Outperforms state-of-the-art methods in simulation convergence, collision, and deadlock rates
- Successfully coordinates both convex and non-convex polytopic robots in dense configurations
- Validated on real-world mobile furniture hardware for room reconfiguration and wheelchair path clearing
- Maintains real-time performance with lower computational overhead than optimization-based approaches
Why it matters
Enables reliable, real-time coordination of dense mobile robot swarms for practical assistive indoor environments, directly benefiting elderly and mobility-impaired users.
Abstract
We explore the use of a mobile furniture swarm that are intended to assist users with limited mobility in their daily indoor activities. We focus on the multi-robot coordination problem when a dense target pose configuration is required, such as in an apartment setting. In those cases, the convergence of one robot to the target can be significantly affected by neighboring robots with specific shapes. In this letter, we propose a solution, named Velocity Potential Field Modulation (VPFM), to deal with the dense coordination problem of a polytopic swarm in a decen- tralized manner. We adapt our method to assistive applications, such as room reconfigurations and facilitating indoor movement of wheelchair users. We evaluate the performance of our method in simulations and on real-world mobile furniture hardware, demonstrating its effectiveness and real-time performance.