A walking robotic hand must use the same fingers to move its body, support its weight, and interact with the environment. We show how an anthropomorphic hand can learn these skills while retaining its finger design and position controller. Onboard power and computation make the platform self-contained. Our reinforcemen...
Amirhossein Kazemipour, He-Hui Zheng, Robert K. Katzschmann· 0 citations
Complex tasks for underwater robots remain limited by the capabilities of their controllers. Learning a better one for a soft, underactuated robotic fish trades simulator cost against fidelity. We show that an intentionally low-fidelity simulator is enough: a stateless, quasi-steady fluid model with no wake and no adde...
Liam Maloney, Simon Ramchandani, M. Y. Michelis et al.· 0 citations
This research presents an embodied control approach based on real-time task Jacobian estimation of the combined hand and object system on the physical robot and showcases an alternative to compute- and data-heavy approaches such as RL and IL for achieving dexterous manipulation through computationally simple and data-e...
Kai Stewart, Yasunori Toshimitsu, Robert K. Katzschmann· 0 citations
The Sampling-Based Retargeter (SBR) is introduced, a novel gradient-free retargeting method drawn from the rich literature of sampling-based control and explicitly designed for low-jitter, real-time kinematic retargeting.
R. J. Malate, Erik Bauer, Norica Bacuieti et al.· arXiv.org· 1 citation
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