Adaptive cancellation of self-generated sensory signals in a whisking robot

Anderson, S., Pearson, M., Pipe, A. G., Prescott, T. J., Dean, P. and Porrill, J. (2010) Adaptive cancellation of self-generated sensory signals in a whisking robot. IEEE Transactions on Robotics, 26 (6). pp. 1065-1076. ISSN 1552-3098 Available from:

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Sensory signals are often caused by one’s own active movements. This raises a problem of discriminating between self-generated sensory signals and signals generated by the external world. Such discrimination is of general importance for robotic systems, where operational robustness is dependent on correct interpretation of sensory signals. Here we investigate this problem in the context of a whiskered robot. The whisker sensory signal comprises two components: one due to contact with an object (externally-generated) and another due to active movement of the whisker (self-generated). We propose a solution to this discrimination problem based on adaptive noise cancellation, where the robot learns to predict the sensory consequences of its own movements using an adaptive filter. The filter inputs (copy of motor commands) are transformed by Laguerre functions instead of the often-used tapped-delay line, which reduces model order and therefore computational complexity. Results from a contact detection task demonstrate that false positives are significantly reduced using the proposed scheme.

Item Type:Article
Additional Information:(c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.
Uncontrolled Keywords:learning and adaptive systems, neurorobotics, force and tactile sensing, noise cancellation, laguerre functions
ID Code:16000
Deposited By: Dr M. Pearson
Deposited On:21 Nov 2011 14:45
Last Modified:29 Dec 2016 12:48

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