9 papers
Advances, challenges, and opportunities for legged robots
Jonas Frey, MatÃas Mattamala, Hae-Won Park +5
Humanoid and quadrupedal robots have the potential to revolutionize the way we work, interact, and coexist with intelligent machines. To understand their effects on society and how…
TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer
Arunim Joarder, Arjun Bhardwaj, René Zurbrügg +6
Tactile sensing provides direct measurements of contact interactions that are essential for robotic manipulation. However, current simulators lack the fidelity to faithfully model…
ViserDex: Visual Sim-to-Real for Robust Dexterous In-hand Reorientation
Arjun Bhardwaj, Maximum Wilder-Smith, Mayank Mittal +2
In-hand object reorientation requires precise estimation of the object pose to handle complex task dynamics. While RGB sensing offers rich semantic cues for pose tracking, existing…
DeFM: Learning Foundation Representations from Depth for Robotics
Manthan Patel, Jonas Frey, Mayank Mittal +5
Depth sensors are widely deployed across robotic platforms, and advances in fast, high-fidelity depth simulation have enabled robotic policies trained on depth observations to achi…
Dynamic object goal pushing with mobile manipulators through model-free constrained reinforcement learning
Ioannis Dadiotis, Mayank Mittal, Nikos Tsagarakis +1
Non-prehensile pushing to move and reorient objects to a goal is a versatile loco-manipulation skill. In the real world, the object's physical properties and friction with the floo…
RSL-RL: A Learning Library for Robotics Research
Clemens Schwarke, Mayank Mittal, Nikita Rudin +2
RSL-RL is an open-source Reinforcement Learning library tailored to the specific needs of the robotics community. Unlike broad general-purpose frameworks, its design philosophy pri…