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Behavior-Based Primitives for Articulated Control

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4 Author(s)

Our previous work has demonstrated how biologicallyinspired behaviors can serve as an effective substrate for control, representation, and learning in mobile robots and multi-robot systems, in order to generate adaptive individual and group behavior. In this paper, we expand the behavior-based approach to the domain of manipulator control, and demonstrate firsi results in applying biological inspiration to a 20 degree-offreedom humanoid dynamical torso simulation.

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