Chaotic exploration and learning of locomotion behaviours

Shim, Yoonsik and Husbands, Phil (2012) Chaotic exploration and learning of locomotion behaviours. Neural Computation, 24 (8). pp. 2185-2222. ISSN 0899-7667

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Abstract

We present a general and fully dynamic neural system, which exploits intrinsic chaotic dynamics, for the real-time goal-directed exploration and learning of the possible locomotion patterns of an articulated robot of an arbitrary morphology in an unknown environment. The controller is modeled as a network of neural oscillators that are initially coupled only through physical embodiment, and goal-directed exploration of coordinated motor patterns is achieved by chaotic search using adaptive bifurcation. The phase space of the indirectly coupled neural-body-environment system contains multiple transient or permanent self-organized dynamics, each of which is a candidate for a locomotion behavior. The adaptive bifurcation enables the system orbit to wander through various phase-coordinated states, using its intrinsic chaotic dynamics as a driving force, and stabilizes on to one of the states matching the given goal criteria. In order to improve the sustainability of useful transient patterns, sensory homeostasis has been introduced, which results in an increased diversity of motor outputs, thus achieving multiscale exploration. A rhythmic pattern discovered by this process is memorized and sustained by changing the wiring between initially disconnected oscillators using an adaptive synchronization method. Our results show that the novel neurorobotic system is able to create and learn multiple locomotion behaviors for a wide range of body configurations and physical environments and can readapt in realtime after sustaining damage.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Q Science > QP Physiology > QP0351 Neurophysiology and neuropsychology > QP0361 Nervous system
T Technology > TJ Mechanical engineering and machinery > TJ0210.2 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General)
T Technology > TJ Mechanical engineering and machinery > TJ0212 Control engineering systems. Automatic machinery (General)
Depositing User: Phil Husbands
Date Deposited: 07 Aug 2012 09:27
Last Modified: 07 Mar 2017 05:42
URI: http://sro.sussex.ac.uk/id/eprint/40210

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