3 papers
cs.AI2026
Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics
Leonard Hinckeldey, Elliot Fosong, Rimvydas Rubavicius +6
As embodied autonomous systems capable of assisting humans in daily activities remain a major goal for robotics, efficient and appropriate reinforcement learning (RL) simulation te…
cs.RO2026
roto 2.0: The Robot Tactile Olympiad
Elle Miller, Jayaram Reddy, Ayush Deshmukh +4
Tactile-based reinforcement learning (RL) is currently hindered by fragmented research and a focus on over-saturated orientation tasks. We introduce v2 of the Robot Tactile Olympia…
cs.RO2025
Enhancing Tactile-based Reinforcement Learning for Robotic Control
Elle Miller, Trevor McInroe, David Abel +2
Achieving safe, reliable real-world robotic manipulation requires agents to evolve beyond vision and incorporate tactile sensing to overcome sensory deficits and reliance on ideali…