Tac-Man: Tactile-Informed Prior-Free Manipulation of Articulated Objects

IEEE Transactions on Robotics (T-RO) 2024
1Institute for Artificial Intelligence, Peking University 2State Key Lab of General AI, BIGAI
3Department of Automation, Tsinghua University 4College of Engineering, Peking University
5Center for Advanced Robotics @ Queen Mary, School of Engineering and Materials Science, Queen Mary University of London
*Equal Contributor Corresponding Author
Teaser

Tactile-informed prior-free manipulation of articulated objects.

Integrating robotics into human-centric environments such as homes, necessitates advanced manipulation skills as robotic devices will need to engage with articulated objects like doors and drawers. Key challenges in robotic manipulation are the unpredictability and diversity of these objects' internal structures, which render models based on priors, both explicit and implicit, inadequate. Their reliability is significantly diminished by pre-interaction ambiguities, imperfect structural parameters, encounters with unknown objects, and unforeseen disturbances. Here, we present a prior-free strategy, Tac-Man, focusing on maintaining stable robot-object contact during manipulation. Utilizing tactile feedback, but independent of object priors, Tac-Man enables robots to proficiently handle a variety of articulated objects, including those with complex joints, even when influenced by unexpected disturbances. Advancements in tactile-informed approaches significantly expand the scope of robotic applications in human-centric environments, particularly where accurate models are difficult to obtain.

Supplementary Videos

manipulation trajectories in the teaser figure

manipulation under ambiguous priors

manipulation under imperfect priors

manipulation under unknown priors

manipulation under obsolescent priors

simulation studies

Acknowledgement

We thank Hongjie Li (PKU), Yida Niu (PKU), and Zimo He (PKU) for setting up the experiments; Prof. Hao Dong (PKU), Zeyi Li (PKU), and Ruihai Wu (PKU) for setting up the Franka Robot; Dr. Chi Zhang (BIGAI) and Dr. Muzhi Han (UCLA) for insightful discussions; and Mr. Mish Toszeghi (QMUL) for meticulously proofreading our manuscript. This work is supported in part by the National Science and Technology Major Project (2022ZD0114900), the National Natural Science Foundation of China (62376031), the Beijing Nova Program, the State Key Lab of General AI at Peking University, the PKU-BingJi Joint Laboratory for Artificial Intelligence, the National Comprehensive Experimental Base for Governance of Intelligent Society, Wuhan East Lake High-Tech Development Zone, and the Horizon Europe Framework through the PALPABLE project (101092518).

BibTeX

@article{zhao2024tac,
  title={Tac-Man: Tactile-Informed Prior-Free Manipulation of Articulated Objects},
  author={Zhao, Zihang and Li, Yuyang and Li, Wanlin and Qi, Zhenghao and Ruan, Lecheng and Zhu, Yixin and Althoefer, Kaspar},
  journal={IEEE Trasactions on Robotics (T-RO)},
  year={2024}
}