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Learning the reachable space of a humanoid robot: A bio-inspired approach

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5 Author(s)
Jamone, L. ; Fac. of Sci. & Eng., Waseda Univ., Tokyo, Japan ; Natale, L. ; Hashimoto, K. ; Sandini, G.
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In this paper we describe how a humanoid robot can learn a representation of its own reachable space from motor experience: a Reachable Space Map. The map provides information about the reachability of a visually detected object (i.e. a 3D point in space). We propose a bio-inspired solution in which the map is built in a gaze-centered reference frame: the position of a point in space is encoded with the motor configuration of the robot head and eyes which allows the fixation of that point. We provide experimental results in which a simulated humanoid robot learns this map autonomously and we discuss how the map can be used for planning whole-body and bimanual reaching.

Published in:

Biomedical Robotics and Biomechatronics (BioRob), 2012 4th IEEE RAS & EMBS International Conference on

Date of Conference:

24-27 June 2012