Aero Hand Open is a tendon‑driven, anthropomorphic hand designed for affordable, simulation‑ready dexterous manipulation. The release includes a realistic simulation model of the cable transmission, an identified actuation map that links motor commands to joint motions (including thumb coupling), and a reinforcement‑learning package that trains policies entirely in simulation. These components enable policies to run on the physical hand without fine‑tuning or state estimation.
By Nan Wang, Mohit Yadav, Jonathan Wulff, Aidan Rosenbaum, Kezhou Chen, Yuvan Sharma, Xu Dong, Yiwei Tao
arXiv:2610.17161v1 Announce Type: cross
Abstract: Teleoperation is widely used to collect high-quality demonstrations for robot learning. Dexterous manipulation, however, requires coordinated control...
By Ying Yuan, David Held, Jitendra Malik, Haozhi Qi
SoTa is a low‑cost, capacitive tactile skin that offers full‑hand coverage for both humans and robots, featuring a shared layout of 202 taxels across finger and palm regions. The multilayer design with fabric electrodes allows in‑house fabrication for under $10 in materials, and the sensor maintains over 97% of its response after 10,000 loading‑unloading cycles and 1,280 tight‑fist folds. Using SoTa, human‑robot co‑training improves in‑distribution success on three contact‑rich manipulation tasks, and adding human demonstrations more than doubles mean success across eight evaluation conditions, from 22.8% to 45.9%, including all out‑of‑distribution scenarios.
By Jingyun Yang, Baiyu Shi, Timothy Yu, Haitian Liu, Alberta Longhini, Weichen Wang, Rika Antonova, Zhenan Bao, Jeannette Bohg
GOTT is a reach‑acquire‑move framework that uses a single cross‑embodiment contact‑acquisition primitive to enable dexterous manipulation across different robot embodiments. The system first positions the hand near a task‑relevant contact region, then the shared closed‑loop primitive establishes stable contact, after which a pose‑conditioned controller tracks the desired object motion. Experiments in simulation and on real robots demonstrate that GOTT reliably establishes robust contact across diverse objects, arm‑hand platforms, and both seen and unseen hand morphologies, and consistently improves end‑to‑end task success compared to open‑loop grasp execution.
By Yulin Liu, Lai Wei, Yen-Jen Wang, Akash Sharma, Pieter Abbeel, Henrik I. Christensen, Haozhi Qi
arXiv:2606. 12728v2 Announce Type: replace-cross Abstract: Most learned dexterous grasp generators relegate contact forces to a downstream verification step, so a kinematically-plausible pose can still violate the conditions for a stable physical grasp.
By Clinton Enwerem, John S. Baras, Calin Belta
arXiv:2610.14372v1 Announce Type: cross
Abstract: Dexterous robot hands can receive useful motion intent from teleoperation or learned policies, but successful execution also depends on contact decis...
By Weikang Wan, Zeyu Lai, Jianyu Hou, Yuchen Zhou, Jiawei Fu, Henrik I Christensen, Hao Su
arXiv:2606. 17394v1 Announce Type: cross Abstract: Adaptation to damages and in-situ physical repairs is essential for long-term robot autonomy, yet challenging outside of narrowly defined and well-anticipated bounds.
By James Avtges, Jake Ketchum, Helena Young, Taekyoung Kim, Ryan Truby, Todd Murphey
arXiv:2604.14944v3 Announce Type: replace-cross
Abstract: We present HRDexDB, a real-world 4D dexterous grasping dataset capturing 3D hand-object interaction trajectories over time across five embodi...
By Jongbin Lim, Taeyun Ha, Seongho Cha, Kanghyeon Cho, Mingi Choi, Subin Jeon, Jisoo Kim, Byungjun Kim, Hanbyul Joo
arXiv:2609.15726v1 Announce Type: cross
Abstract: Tactile sensing provides contact information that can be difficult to infer from vision alone, but tactile hardware for dexterous hands has not conve...
By Zhenjie Yang, Yideng Zhang, Dongjie Zhang, Chenyu Jiang, Xianshuai Liu, Yufeng Li, Zuhao Ge, Xingyu Jiao, Zheng Zhang, Kaiyu He, He Wang, Yuwen Zhong, Yi Deng, Muyun Jiang, Xianliang Huang, Haisheng Su, Donghang Zhang, Jian Zhang, Xue Yang, Hongyang Li, Zuxuan Wu, Yu-Gang Jiang, Xiaosong Jia, Junchi Yan
arXiv:2606. 14218v1 Announce Type: cross Abstract: For robots to work safely in household environments, they need to be compliant and react to torque and force feedback during contact.
By Litian Liang, Jingxi Xu, Xinda Qi, Yujun Cai, Houzhu Ding, Luqi Wang, Zhixin Sun, Jyh-Herng Chow, Ming Yang, Mark Cutkosky
We’ve trained a human-like robot hand to manipulate physical objects with unprecedented dexterity.
arXiv:2606. 14561v1 Announce Type: cross Abstract: Robotics manipulation research increasingly focuses on two-finger parallel grippers for their effectiveness, affordability, and ease of teleoperation.
By Francesco Capuano, Maximilian Eberlein, Fabrice Bourquin, Clemens Claudio Christoph