2 citations · 2 across the 10 of their papers we have counts for
10 papers
Cross-Embodiment Robot Manipulation via a Unified Hand Action Space
Luis Felipe Casas, Robert Teal, Keval Shah +3
Robot manipulation policies are typically tied to specific robotic hand embodiments, limiting the transfer of learned behaviors across platforms with different kinematic structures…
VLA-REPLICA: A Low-Cost, Reproducible Benchmark for Real-World Evaluation of Vision-Language-Action Models
Alex S. Huang, Jiahui Zhang, Shiqing Tang +1
Vision-Language-Action (VLA) models have shown strong promise for general-purpose robotic manipulation, but their real-world evaluation remains limited by a lack of accessible, rep…
The Great March 100: 100 Detail-oriented Tasks for Evaluating Embodied AI Agents
Ziyu Wang, Chenyuan Liu, Yushun Xiang +16
Recently, with the rapid development of robot learning and imitation learning, numerous datasets and methods have emerged. However, these datasets and their task designs often lack…
Where to Touch, How to Contact: A Hierarchical RL-MPC Framework for Geometry-Aware Sim-to-Real Manipulation
Zhixian Xie, Yu Xiang, Michael Posa +1
A key challenge in contact-rich dexterous manipulation is the need to jointly reason over global geometry and nonsmooth contact dynamics. End-to-end policies bypass this complexity…
OpenEgo: A Large-Scale Multimodal Egocentric Dataset for Dexterous Manipulation
Ahad Jawaid, Yu Xiang
Egocentric human videos provide scalable demonstrations for imitation learning, but existing corpora often lack either fine-grained, temporally localized action descriptions or dex…
V-HOP: Visuo-Haptic 6D Object Pose Tracking
Hongyu Li, Mingxi Jia, Tuluhan Akbulut +3
Humans naturally integrate vision and haptics for robust object perception during manipulation. The loss of either modality significantly degrades performance. Inspired by this mul…
iTeach: In the Wild Interactive Teaching for Failure-Driven Adaptation of Robot Perception
Jishnu Jaykumar P, Cole Salvato, Vinaya Bomnale +4
We present iTeach, a deployable system that lets any co-located human fix a robot's perception failures on the spot without expertise, a workstation, or offline retraining. The ope…
RobotFingerPrint: Unified Gripper Coordinate Space for Multi-Gripper Grasp Synthesis and Transfer
Ninad Khargonkar, Luis Felipe Casas, Balakrishnan Prabhakaran +1
We introduce a novel grasp representation named the Unified Gripper Coordinate Space (UGCS) for grasp synthesis and grasp transfer. Our representation leverages spherical coordinat…
RISeg: Robot Interactive Object Segmentation via Body Frame-Invariant Features
Howard H. Qian, Yangxiao Lu, Kejia Ren +4
In order to successfully perform manipulation tasks in new environments, such as grasping, robots must be proficient in segmenting unseen objects from the background and/or other o…
MultiGripperGrasp: A Dataset for Robotic Grasping from Parallel Jaw Grippers to Dexterous Hands
Luis Felipe Casas, Ninad Khargonkar, Balakrishnan Prabhakaran +1
We introduce a large-scale dataset named MultiGripperGrasp for robotic grasping. Our dataset contains 30.4M grasps from 11 grippers for 345 objects. These grippers range from two-f…