4 papers · 1 filter
Curriculum Imitation Learning of Distributed Multi-Robot Policies
Jesús Roche, Eduardo Sebastián, Eduardo Montijano
Learning control policies for multi-robot systems (MRS) remains a major challenge due to long-term coordination and the difficulty of obtaining realistic training data. In this wor…
Physics-Informed Multi-Agent Reinforcement Learning for Distributed Multi-Robot Problems
Eduardo Sebastian, Thai Duong, Nikolay Atanasov +2
The networked nature of multi-robot systems presents challenges in the context of multi-agent reinforcement learning. Centralized control policies do not scale with increasing numb…
AVOCADO: Adaptive Optimal Collision Avoidance driven by Opinion
Diego Martinez-Baselga, Eduardo Sebastián, Eduardo Montijano +3
We present AVOCADO (AdaptiVe Optimal Collision Avoidance Driven by Opinion), a novel navigation approach to address holonomic robot collision avoidance when the robot does not know…
Gen-Swarms: Adapting Deep Generative Models to Swarms of Drones
Carlos Plou, Pablo Pueyo, Ruben Martinez-Cantin +3
Gen-Swarms is an innovative method that leverages and combines the capabilities of deep generative models with reactive navigation algorithms to automate the creation of drone show…