20 papers
BayesContact: Uncertain Pose Estimation via Visuo-Tactile Proposals and Simulation-based Inference
Aditya Kamireddypalli, Matias Mattamala, Joao Moura +3
Contact-rich manipulation requires pose estimates that are often more accurate than what depth-only sensing provides. Existing methods, relying on vision and contact, employ costly…
Optimal Transport Q-Learning for Flow Policy Steering and Acceleration
Andreas Sochopoulos, Esmeralda S. Whitammer, Nikolaos Tsagkas +3
Diffusion and flow policies have recently demonstrated remarkable performance in robotic applications by accurately capturing multimodal robot trajectory distributions, especially…
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…
Attentive Feature Aggregation or: How Policies Learn to Stop Worrying about Robustness and Attend to Task-Relevant Visual Cues
Nikolaos Tsagkas, Andreas Sochopoulos, Duolikun Danier +4
The adoption of pre-trained visual representations (PVRs), leveraging features from large-scale vision models, has become a popular paradigm for training visuomotor policies. Howev…
Online Estimation and Manipulation of Articulated Objects
Russell Buchanan, Adrian Röfer, João Moura +2
From refrigerators to kitchen drawers, humans interact with articulated objects effortlessly every day while completing household chores. For automating these tasks, service robots…
Efficient Learning of Object Placement with Intra-Category Transfer
Adrian Röfer, Russell Buchanan, Max Argus +2
Efficient learning from demonstration for long-horizon tasks remains an open challenge in robotics. While significant effort has been directed toward learning trajectories, a recen…