A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle

Erfu Yang, Amir Hussain, Kevin Gurney

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

2 Citations (Scopus)

Abstract

This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which imply no single stabilizing controller solution is possible by time-invariant smooth state feedback. To allow the BG make the correct controller selection from a family of candidate motion controllers, a fuzzy logic-based salience model using reference and tracking error only is developed, and applied in a soft switching control mechanism. To demonstrate the effectiveness of our approach for motion tracking control, we show effective control for a circular trajectory tracking application. The performance and advantages of the proposed fuzzy salience model and the BG-based soft switching control scheme against a traditional single control method are compared.

Original languageEnglish
Title of host publicationAdvances in Brain Inspired Cognitive Systems
Subtitle of host publication6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings
EditorsDerong Liu, Cesare Alippi, Dongbin Zhao, Amir Hussain
Place of PublicationBerlin
Pages245-254
Number of pages10
DOIs
Publication statusPublished - 28 May 2013
Event6th International Conference on Brain Inspired Cognitive Systems, BICS 2013 - Beijing, United Kingdom
Duration: 9 Jun 201311 Jun 2013

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume7888
ISSN (Print)0302-9743

Conference

Conference6th International Conference on Brain Inspired Cognitive Systems, BICS 2013
CountryUnited Kingdom
CityBeijing
Period9/06/1311/06/13

Fingerprint

Switching Control
Autonomous Vehicles
Motion Control
Motion control
Railroad cars
Controller
Nonholonomic Constraints
Motion Tracking
Trajectory Tracking
State Constraints
Reference Model
Tracking Control
Fuzzy Model
State Feedback
Controllers
Fuzzy Logic
Imply
Invariant
Motion
State feedback

Keywords

  • action selection
  • autonomous vehicles
  • basal ganglia
  • brain-inspired computing
  • cognitive computation
  • fuzzy logic
  • motion control
  • multiple controller systems
  • soft switching

Cite this

Yang, E., Hussain, A., & Gurney, K. (2013). A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. In D. Liu, C. Alippi, D. Zhao, & A. Hussain (Eds.), Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings (pp. 245-254). (Lecture Notes in Computer Science; Vol. 7888). Berlin. https://doi.org/10.1007/978-3-642-38786-9_28
Yang, Erfu ; Hussain, Amir ; Gurney, Kevin. / A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. editor / Derong Liu ; Cesare Alippi ; Dongbin Zhao ; Amir Hussain. Berlin, 2013. pp. 245-254 (Lecture Notes in Computer Science).
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abstract = "This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which imply no single stabilizing controller solution is possible by time-invariant smooth state feedback. To allow the BG make the correct controller selection from a family of candidate motion controllers, a fuzzy logic-based salience model using reference and tracking error only is developed, and applied in a soft switching control mechanism. To demonstrate the effectiveness of our approach for motion tracking control, we show effective control for a circular trajectory tracking application. The performance and advantages of the proposed fuzzy salience model and the BG-based soft switching control scheme against a traditional single control method are compared.",
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Yang, E, Hussain, A & Gurney, K 2013, A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. in D Liu, C Alippi, D Zhao & A Hussain (eds), Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. Lecture Notes in Computer Science, vol. 7888, Berlin, pp. 245-254, 6th International Conference on Brain Inspired Cognitive Systems, BICS 2013, Beijing, United Kingdom, 9/06/13. https://doi.org/10.1007/978-3-642-38786-9_28

A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. / Yang, Erfu; Hussain, Amir; Gurney, Kevin.

Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. ed. / Derong Liu; Cesare Alippi; Dongbin Zhao; Amir Hussain. Berlin, 2013. p. 245-254 (Lecture Notes in Computer Science; Vol. 7888).

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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N2 - This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which imply no single stabilizing controller solution is possible by time-invariant smooth state feedback. To allow the BG make the correct controller selection from a family of candidate motion controllers, a fuzzy logic-based salience model using reference and tracking error only is developed, and applied in a soft switching control mechanism. To demonstrate the effectiveness of our approach for motion tracking control, we show effective control for a circular trajectory tracking application. The performance and advantages of the proposed fuzzy salience model and the BG-based soft switching control scheme against a traditional single control method are compared.

AB - This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which imply no single stabilizing controller solution is possible by time-invariant smooth state feedback. To allow the BG make the correct controller selection from a family of candidate motion controllers, a fuzzy logic-based salience model using reference and tracking error only is developed, and applied in a soft switching control mechanism. To demonstrate the effectiveness of our approach for motion tracking control, we show effective control for a circular trajectory tracking application. The performance and advantages of the proposed fuzzy salience model and the BG-based soft switching control scheme against a traditional single control method are compared.

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Yang E, Hussain A, Gurney K. A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. In Liu D, Alippi C, Zhao D, Hussain A, editors, Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings. Berlin. 2013. p. 245-254. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-38786-9_28