38 citations · 129 across the 17 of their papers we have counts for
5 papers · 1 filter
Grasp-MPC: Closed-Loop Visual Grasping via Value-Guided Model Predictive Control
Jun Yamada, Adithyavairavan Murali, Ajay Mandlekar +3
Grasping of diverse objects in unstructured environments remains a significant challenge. Open-loop grasping methods, effective in controlled settings, struggle in cluttered enviro…
3D-Generalist: Self-Improving Vision-Language-Action Models for Crafting 3D Worlds
Fan-Yun Sun, Shengguang Wu, Christian Jacobsen +13
Despite large-scale pretraining endowing models with language and vision reasoning capabilities, improving their spatial reasoning capability remains challenging due to the lack of…
Robot Policy Evaluation for Sim-to-Real Transfer: A Benchmarking Perspective
Xuning Yang, Clemens Eppner, Jonathan Tremblay +3
Current vision-based robotics simulation benchmarks have significantly advanced robotic manipulation research. However, robotics is fundamentally a real-world problem, and evaluati…
GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training
Adithyavairavan Murali, Balakumar Sundaralingam, Yu-Wei Chao +7
Grasping is a fundamental robot skill, yet despite significant research advancements, learning-based 6-DOF grasping approaches are still not turnkey and struggle to generalize acro…
RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies
Pranav Atreya, Karl Pertsch, Tony Lee +29
Comprehensive, unbiased, and comparable evaluation of modern generalist policies is uniquely challenging: existing approaches for robot benchmarking typically rely on heavy standar…