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A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing

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A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing. / Wilson, E.D.; Assaf, T.; Rossiter, J.M. et al.
In: Interface, Vol. 18, No. 174, 27.01.2021.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Wilson, ED, Assaf, T, Rossiter, JM, Dean, P, Porrill, J, Anderson, SR & Pearson, MJ 2021, 'A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing', Interface, vol. 18, no. 174. https://doi.org/10.1098/rsif.2020.0750

APA

Wilson, E. D., Assaf, T., Rossiter, J. M., Dean, P., Porrill, J., Anderson, S. R., & Pearson, M. J. (2021). A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing. Interface, 18(174). https://doi.org/10.1098/rsif.2020.0750

Vancouver

Wilson ED, Assaf T, Rossiter JM, Dean P, Porrill J, Anderson SR et al. A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing. Interface. 2021 Jan 27;18(174). doi: 10.1098/rsif.2020.0750

Author

Wilson, E.D. ; Assaf, T. ; Rossiter, J.M. et al. / A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing. In: Interface. 2021 ; Vol. 18, No. 174.

Bibtex

@article{42d557dc4e694baf9b6b352ef09560f4,
title = "A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing",
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.",
keywords = "adaptive filter, bioinspired robot control, cerebellar chip, cerebellum, soft robotics",
author = "E.D. Wilson and T. Assaf and J.M. Rossiter and P. Dean and J. Porrill and S.R. Anderson and M.J. Pearson",
year = "2021",
month = jan,
day = "27",
doi = "10.1098/rsif.2020.0750",
language = "English",
volume = "18",
journal = "Interface",
issn = "1742-5689",
publisher = "Royal Society of London",
number = "174",

}

RIS

TY - JOUR

T1 - A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing

AU - Wilson, E.D.

AU - Assaf, T.

AU - Rossiter, J.M.

AU - Dean, P.

AU - Porrill, J.

AU - Anderson, S.R.

AU - Pearson, M.J.

PY - 2021/1/27

Y1 - 2021/1/27

N2 - 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.

AB - 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.

KW - adaptive filter

KW - bioinspired robot control

KW - cerebellar chip

KW - cerebellum

KW - soft robotics

U2 - 10.1098/rsif.2020.0750

DO - 10.1098/rsif.2020.0750

M3 - Journal article

VL - 18

JO - Interface

JF - Interface

SN - 1742-5689

IS - 174

ER -