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Abstract

In this paper we present our work on integrating a locomotion controller based on central pattern generator (CPG) and a motion planning algorithm using artificial potential fields for a non-holonomic crawling humanoid robot, the iCub. We also integrated a vision tracker and an inverse kinematics solver to perform reaching tasks. We study the influence of the various parameters of the potential field equations on the performance of the system and prove the efficiency of our framework by testing it on a physics-based robotics simulator and partially on the real iCub.

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