///Towards Safe and Robust Behavior Mixing for Multi-Robot Systems
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PhD Speaking Qualifier


Wenhao Luo PhD Student Robotics Institute,
Carnegie Mellon University
Monday, April 22
12:00 pm
- 1:00 pm
GHC 8102
Towards Safe and Robust Behavior Mixing for Multi-Robot Systems

Multi-robot systems have been widely studied for extending its capability of accomplishing complex tasks through cooperative behaviors. In large-scale multi-robot behavior mixing, the heterogeneous robotic team executes simultaneously multiple behaviors or sequences of behaviors with various task-prescribed controllers in real time to increase efficiency in parallel tasks. Key to the success of behavior mixing lies in the ability to retain safety (e.g. no inter-robot collisions) and robustness (e.g. dynamic network connectivity, failure of robots) to enable smooth execution and coordination among robots. In this talk, I will present our most recent works on a unified optimization-based control framework synthesizing the original behavior-prescribed multi-robot controllers to generate provably collision-free and robustly connected multi-robot behaviors. The proposed control synthesis framework can be applied to any multi-robot controllers to ensure safety and connectivity in a minimally invasive manner, yielding significantly increased flexibility for large-scale behavior mixing. We will provide simulation results on at least 40 robots executing multiple behaviors to demonstrate the effectiveness and efficiency of the proposed methods.

Katia Sycara (advisor)
Maxim Likhachev
George Kantor
Jayanth Krishna Mogali