Wilson, E.D., Assaf, T., Rossiter, J.M. et al. (4 more authors) (2021) A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing. Journal of The Royal Society Interface, 18 (174). 20200750. ISSN 1742-5689
Abstract
The cerebellum is a neural structure essential for learning, which is connected via multiple zones to many different regions of the brain, and is thought to improve human performance in a large range of sensory, motor and even cognitive processing tasks. An intriguing possibility for the control of complex robotic systems would be to develop an artificial cerebellar chip with multiple zones that could be similarly connected to a variety of subsystems to optimize performance. The novel aim of this paper, therefore, is to propose and investigate a multizone cerebellar chip applied to a range of tasks in robot adaptive control and sensorimotor processing. The multizone cerebellar chip was evaluated using a custom robotic platform consisting of an array of tactile sensors driven by dielectric electroactive polymers mounted upon a standard industrial robot arm. The results demonstrate that the performance in each task was improved by the concurrent, stable learning in each cerebellar zone. This paper, therefore, provides the first empirical demonstration that a synthetic, multizone, cerebellar chip could be embodied within existing robotic systems to improve performance in a diverse range of tasks, much like the cerebellum in a biological system.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2021 The Author(s). Published by the Royal Society. This is an author-produced version of a paper subsequently published in Journal of the Royal Society, Interface. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | cerebellum; adaptive filter; soft robotics; bioinspired robot control; cerebellar chip |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/I032533/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Mar 2021 12:32 |
Last Modified: | 08 Mar 2021 12:38 |
Status: | Published |
Publisher: | The Royal Society |
Refereed: | Yes |
Identification Number: | 10.1098/rsif.2020.0750 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:171926 |