Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises …
The world outside our laboratories seldom conforms to the assumptions of our models. This is especially true for dynamics models used in control and motion planning for complex high …
M Yu, H Zhong, X Li - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
The shape control of deformable linear objects (DLOs) is challenging, since it is difficult to obtain the deformation models. Previous studies often approximate the models in purely …
Sampling-based methods are widely adopted solutions for robot motion planning. The methods are straightforward to implement, effective in practice for many robotic systems. It is …
We present a method for feedback motion planning of systems with unknown dynamics which provides probabilistic guarantees on safety, reachability, and goal stability. To find a …
F Gu, Y Zhou, Z Wang, S Jiang, B He - arXiv preprint arXiv:2312.10419, 2023 - arxiv.org
Deformable object manipulation (DOM) for robots has a wide range of applications in various fields such as industrial, service and health care sectors. However, compared to …
The success of deep learning depends heavily on the availability of large datasets, but in robotic manipulation there are many learning problems for which such datasets do not exist …
F Liu, E Su, J Lu, M Li, MC Yip - IEEE Robotics and Automation …, 2023 - ieeexplore.ieee.org
Robot manipulation of rope-like objects is an interesting problem with some critical applications, such as autonomous robotic suturing. Solving for and controlling rope is …
In order to efficiently learn a dynamics model for a task in a new environment, one can adapt a model learned in a similar source environment. However, existing adaptation methods can …