Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin

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Title: Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin
Authors: Calandra, R
Ivaldi, S
Deisenroth, MP
Peters, J
Item Type: Conference Paper
Abstract: © 2015 IEEE.Whole-body control in unknown environments is challenging: Unforeseen contacts with obstacles can lead to poor tracking performance and potential physical damages of the robot. Hence, a whole-body control approach for future humanoid robots in (partially) unknown environments needs to take contact sensing into account, e.g., by means of artificial skin. However, translating contacts from skin measurements into physically well-understood quantities can be problematic as the exact position and strength of the contact needs to be converted into torques. In this paper, we suggest an alternative approach that directly learns the mapping from both skin and the joint state to torques. We propose to learn such an inverse dynamics models with contacts using a mixture-of-contacts approach that exploits the linear superimposition of contact forces. The learned model can, making use of uncalibrated tactile sensors, accurately predict the torques needed to compensate for the contact. As a result, tracking of trajectories with obstacles and tactile contact can be executed more accurately. We demonstrate on the humanoid robot iCub that our approach improve the tracking error in presence of dynamic contacts.
Issue Date: 3-Nov-2015
Date of Acceptance: 12-Sep-2015
URI: http://hdl.handle.net/10044/1/26653
Publisher: IEEE
Copyright Statement: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Conference Name: 2015 IEEE-RAS International Conference on Humanoid Robots
Publication Status: Accepted
Start Date: 2015-11-03
Finish Date: 2015-11-05
Conference Place: Seoul, Korea
Appears in Collections:Faculty of Engineering
Computing



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