11 papers
TactX: Learning Shared Tactile Representations Across Diverse Sensors
Junsung Park, Sachin Bhadang, Carmelo Sferrazza +2
Tactile sensors provide critical information for contact-rich manipulation, yet tactile representations and policies remain tightly coupled to each specific sensor, limiting transf…
House of Dextra: Cross-embodied Co-design for Dexterous Hands
Kehlani Fay, Darin Anthony Djapri, Anya Zorin +6
Dexterous manipulation is limited by both control and design, without consensus as to what makes manipulators best for performing dexterous tasks. This raises a fundamental challen…
Generating Robot Hands from Human Demonstrations
Sha Yi, Nicklas Hansen, Xueqian Bai +3
Robot learning has advanced rapidly in learning control, but learning the physical body of a robot remains much more difficult because jointly searching over design and control cre…
TacO: Benchmarking Tactile Sensors for Object Manipulation
Anya Zorin, Zilin Si, Myungsun Park +11
Vision-based learning from demonstrations has achieved remarkable success in enabling robots to perform manipulation tasks and high-level semantic reasoning, yet it remains insuffi…
Long-Horizon Manipulation via Trace-Conditioned VLA Planning
Isabella Liu, An-Chieh Cheng, Rui Yan +7
Long-horizon manipulation remains challenging for vision-language-action (VLA) policies: real tasks are multi-step, progress-dependent, and brittle to compounding execution errors.…
Contact-Aware Neural Dynamics
Changwei Jing, Jai Krishna Bandi, Jianglong Ye +4
High-fidelity physics simulation is essential for scalable robotic learning, but the sim-to-real gap persists, especially for tasks involving complex, dynamic, and discontinuous in…