8 citations · 30 across the 8 of their papers we have counts for
5 papers · 1 filter
Scaling Multi Agent Reinforcement Learning for Underwater Acoustic Tracking via Autonomous Vehicles
Matteo Gallici, Ivan Masmitja, Mario Martín
Autonomous vehicles (AVs) offer a cost-effective solution for scientific missions such as underwater tracking. Reinforcement learning (RL) has emerged as a powerful method for cont…
Morphological Symmetries in Robotics
Daniel Ordoñez-Apraez, Giulio Turrisi, Vladimir Kostic +6
We present a comprehensive framework for studying and leveraging morphological symmetries in robotic systems. These are intrinsic properties of the robot's morphology, frequently o…
On discrete symmetries of robotics systems: A group-theoretic and data-driven analysis
Daniel Ordonez-Apraez, Mario Martin, Antonio Agudo +1
We present a comprehensive study on discrete morphological symmetries of dynamical systems, which are commonly observed in biological and artificial locomoting systems, such as leg…
A reinforcement learning path planning approach for range-only underwater target localization with autonomous vehicles
Ivan Masmitja, Mario Martin, Kakani Katija +2
Underwater target localization using range-only and single-beacon (ROSB) techniques with autonomous vehicles has been used recently to improve the limitations of more complex metho…
An Adaptable Approach to Learn Realistic Legged Locomotion without Examples
Daniel Ordonez-Apraez, Antonio Agudo, Francesc Moreno-Noguer +1
Learning controllers that reproduce legged locomotion in nature has been a long-time goal in robotics and computer graphics. While yielding promising results, recent approaches are…