Taylor D. Niehues — accepted AI-conference papers

2018

Human-Inspired Object Manipulation Control with the Anatomically Correct Testbed Hand

ICRA 2018poster

Dexterous manipulation with robotic hands can be achieved using object-level impedance control strategies, which allow intuitive regulation of object position, external environmental interactions, and grasp forces. However, for grasp stability, object stiffness gains are limited by the inherent comp…

Cited by 2 Source ↗Scholar ↗

2017

Development and validation of modeling framework for interconnected tendon networks in robotic and human fingers

Taylor D. Niehues, Raymond J. King, Ashish D. Deshpande, Sean Keller

ICRA 2017poster

The primary contribution of this work is the development of a generalized modeling methodology for complex tendon systems toward a long-term goal of modeling the mechanical structure of the human finger. The key feature of this model is its ability to predict how muscle forces will transmit through…

Cited by 11 Source ↗Scholar ↗