Developing the cerebellar chip as a general control module for autonomous systems

Emma D. Wilson; Sean R. Anderson; Tareq Assaf; Jonathan M. Rossiter; Martin J. Pearson; John Porrill

doi:10.1007/978-3-662-43645-5_8

Developing the cerebellar chip as a general control module for autonomous systems

Emma D. Wilson, Sean R. Anderson, Tareq Assaf, Jonathan M. Rossiter, Martin J. Pearson, John Porrill

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Abstract

Biological systems have evolved robust, adaptive control strategies to deal with a wide range of control tasks in time varying systems and environments. The cerebellum is the brain structure particularly associated with the control of skilled movements, the advantageous properties of the cerebellum can be exploited for robotic control applications. In this contribution we present a bioinspired cerebellar control algorithm. We extend the existing cerebellar inspired adaptive filter control algorithm, previously applied to plants of specific order, to the control of general n^th order plants. This is done by augmenting the existing cerebellar algorithm with a reference model, a technique used in model reference adaptive control. This augmented cerebellar controller is applied successfully to the simulated control of a general plant, and to the real time control of a dielectric electroactive polymer actuator. This augmented biomimetic control strategy has promise for the control of human-centred robots operating in unstructured environments.

Original language	English
Title of host publication	Towards Autonomous Robotic Systems - 14th Annual Conference, TAROS 2013, Revised Selected Papers
Publisher	Springer Verlag
Pages	53-63
Number of pages	11
ISBN (Print)	9783662436448
DOIs	https://doi.org/10.1007/978-3-662-43645-5_8
Publication status	Published - 31 Dec 2014
Event	14th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2013 - Oxford, UK United Kingdom Duration: 28 Aug 2013 → 30 Aug 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8069 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2013
Country/Territory	UK United Kingdom
City	Oxford
Period	28/08/13 → 30/08/13

Bibliographical note

Funding Information:
This was supported by an EPSRC grant no. EP/IO32533/1, Bioinspired Control of Electro-Active Polymers for Next Generation Soft Robots.

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-662-43645-5_8

Cite this

Wilson, E. D., Anderson, S. R., Assaf, T., Rossiter, J. M., Pearson, M. J., & Porrill, J. (2014). Developing the cerebellar chip as a general control module for autonomous systems. In Towards Autonomous Robotic Systems - 14th Annual Conference, TAROS 2013, Revised Selected Papers (pp. 53-63). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8069 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-662-43645-5_8

Developing the cerebellar chip as a general control module for autonomous systems. / Wilson, Emma D.; Anderson, Sean R.; Assaf, Tareq et al.
Towards Autonomous Robotic Systems - 14th Annual Conference, TAROS 2013, Revised Selected Papers. Springer Verlag, 2014. p. 53-63 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8069 LNAI).

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Wilson, ED, Anderson, SR, Assaf, T, Rossiter, JM, Pearson, MJ & Porrill, J 2014, Developing the cerebellar chip as a general control module for autonomous systems. in Towards Autonomous Robotic Systems - 14th Annual Conference, TAROS 2013, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8069 LNAI, Springer Verlag, pp. 53-63, 14th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2013, Oxford, UK United Kingdom, 28/08/13. https://doi.org/10.1007/978-3-662-43645-5_8

Wilson ED, Anderson SR, Assaf T, Rossiter JM, Pearson MJ, Porrill J. Developing the cerebellar chip as a general control module for autonomous systems. In Towards Autonomous Robotic Systems - 14th Annual Conference, TAROS 2013, Revised Selected Papers. Springer Verlag. 2014. p. 53-63. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-662-43645-5_8

Wilson, Emma D. ; Anderson, Sean R. ; Assaf, Tareq et al. / Developing the cerebellar chip as a general control module for autonomous systems. Towards Autonomous Robotic Systems - 14th Annual Conference, TAROS 2013, Revised Selected Papers. Springer Verlag, 2014. pp. 53-63 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AU - Porrill, John

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AB - Biological systems have evolved robust, adaptive control strategies to deal with a wide range of control tasks in time varying systems and environments. The cerebellum is the brain structure particularly associated with the control of skilled movements, the advantageous properties of the cerebellum can be exploited for robotic control applications. In this contribution we present a bioinspired cerebellar control algorithm. We extend the existing cerebellar inspired adaptive filter control algorithm, previously applied to plants of specific order, to the control of general nth order plants. This is done by augmenting the existing cerebellar algorithm with a reference model, a technique used in model reference adaptive control. This augmented cerebellar controller is applied successfully to the simulated control of a general plant, and to the real time control of a dielectric electroactive polymer actuator. This augmented biomimetic control strategy has promise for the control of human-centred robots operating in unstructured environments.

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Developing the cerebellar chip as a general control module for autonomous systems

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