activity
20162025
most citedMulti-Fingered Robotic Grasping: A Primer

3 citations · 9 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO20252 cited

DextrAH-RGB: Visuomotor Policies to Grasp Anything with Dexterous Hands

Ritvik Singh, Arthur Allshire, Ankur Handa +2

One of the most important, yet challenging, skills for a dexterous robot is grasping a diverse range of objects. Much of the prior work has been limited by speed, generality, or re…

cs.RO2024

23 DoF Grasping Policies from a Raw Point Cloud

Martin Matak, Karl Van Wyk, Tucker Hermans

Coordinating the motion of robots with high degrees of freedom (DoF) to grasp objects gives rise to many challenges. In this paper, we propose a novel imitation learning approach t…

cs.RO2024

AutoMate: Specialist and Generalist Assembly Policies over Diverse Geometries

Bingjie Tang, Iretiayo Akinola, Jie Xu +7

Robotic assembly for high-mixture settings requires adaptivity to diverse parts and poses, which is an open challenge. Meanwhile, in other areas of robotics, large models and sim-t…

cs.RO20241 cited

Geometric Fabrics: a Safe Guiding Medium for Policy Learning

Karl Van Wyk, Ankur Handa, Viktor Makoviychuk +3

Robotics policies are always subjected to complex, second order dynamics that entangle their actions with resulting states. In reinforcement learning (RL) contexts, policies have t…

cs.RO20232 cited

cuRobo: Parallelized Collision-Free Minimum-Jerk Robot Motion Generation

Balakumar Sundaralingam, Siva Kumar Sastry Hari, Adam Fishman +9

This paper explores the problem of collision-free motion generation for manipulators by formulating it as a global motion optimization problem. We develop a parallel optimization t…

cs.RO20231 cited

Fabrics: A Foundationally Stable Medium for Encoding Prior Experience

Nathan Ratliff, Karl Van Wyk

Most dynamics functions are not well-aligned to task requirements. Controllers, therefore, often invert the dynamics and reshape it into something more useful. The learning communi…