Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method

Pernilla Craig; Laurence Aitchison; Nathan F. Lepora

doi:10.1007/978-3-031-20470-8_18

Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method

Pernilla Craig^*, Laurence Aitchison, Nathan F. Lepora

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

1 Citation (Scopus)

Abstract

This work presents a proof of concept implementation of an active inference based control mechanism for tactile sensing systems. Active inference is a theory developed in neuroscience to model decision making in the human brain. Here, we use an active inference framework to successfully complete a localisation task using a biomimetic optical tactile sensor mounted on a robotic arm and tactile stimulus as the environment. The system demonstrated optimal control strategies for action selection and achieved a high degree of accuracy.

Original language	English
Title of host publication	Biomimetic and Biohybrid Systems
Subtitle of host publication	11th International Conference, Living Machines 2022, Proceedings
Editors	Alexander Hunt, Vasiliki Vouloutsi, Kenneth Moses, Roger Quinn, Anna Mura, Tony Prescott, Paul F. Verschure
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	169-181
Number of pages	13
ISBN (Print)	9783031204692
DOIs	https://doi.org/10.1007/978-3-031-20470-8_18
Publication status	Published - 2 Dec 2022
Event	11th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2022 - Virtual, Online Duration: 19 Jul 2022 → 22 Jul 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13548 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2022
City	Virtual, Online
Period	19/07/22 → 22/07/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Localisation
Perceptual inference
Tactile sensing

Access to Document

10.1007/978-3-031-20470-8_18Licence: Unspecified

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Cite this

Craig, P., Aitchison, L., & Lepora, N. F. (2022). Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method. In A. Hunt, V. Vouloutsi, K. Moses, R. Quinn, A. Mura, T. Prescott, & P. F. Verschure (Eds.), Biomimetic and Biohybrid Systems : 11th International Conference, Living Machines 2022, Proceedings (pp. 169-181). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13548 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-20470-8_18

Craig, Pernilla ; Aitchison, Laurence ; Lepora, Nathan F. / Active Inference for Artificial Touch : A Biologically-Plausible Tactile Control Method. Biomimetic and Biohybrid Systems : 11th International Conference, Living Machines 2022, Proceedings. editor / Alexander Hunt ; Vasiliki Vouloutsi ; Kenneth Moses ; Roger Quinn ; Anna Mura ; Tony Prescott ; Paul F. Verschure. Springer Science and Business Media Deutschland GmbH, 2022. pp. 169-181 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This work presents a proof of concept implementation of an active inference based control mechanism for tactile sensing systems. Active inference is a theory developed in neuroscience to model decision making in the human brain. Here, we use an active inference framework to successfully complete a localisation task using a biomimetic optical tactile sensor mounted on a robotic arm and tactile stimulus as the environment. The system demonstrated optimal control strategies for action selection and achieved a high degree of accuracy.",

keywords = "Localisation, Perceptual inference, Tactile sensing",

author = "Pernilla Craig and Laurence Aitchison and Lepora, \{Nathan F.\}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 11th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2022 ; Conference date: 19-07-2022 Through 22-07-2022",

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Craig, P, Aitchison, L & Lepora, NF 2022, Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method. in A Hunt, V Vouloutsi, K Moses, R Quinn, A Mura, T Prescott & PF Verschure (eds), Biomimetic and Biohybrid Systems : 11th International Conference, Living Machines 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13548 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 169-181, 11th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2022, Virtual, Online, 19/07/22. https://doi.org/10.1007/978-3-031-20470-8_18

Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method. / Craig, Pernilla; Aitchison, Laurence ; Lepora, Nathan F.
Biomimetic and Biohybrid Systems : 11th International Conference, Living Machines 2022, Proceedings. ed. / Alexander Hunt; Vasiliki Vouloutsi; Kenneth Moses; Roger Quinn; Anna Mura; Tony Prescott; Paul F. Verschure. Springer Science and Business Media Deutschland GmbH, 2022. p. 169-181 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13548 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Active Inference for Artificial Touch

T2 - 11th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2022

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AU - Aitchison, Laurence

AU - Lepora, Nathan F.

PY - 2022/12/2

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AB - This work presents a proof of concept implementation of an active inference based control mechanism for tactile sensing systems. Active inference is a theory developed in neuroscience to model decision making in the human brain. Here, we use an active inference framework to successfully complete a localisation task using a biomimetic optical tactile sensor mounted on a robotic arm and tactile stimulus as the environment. The system demonstrated optimal control strategies for action selection and achieved a high degree of accuracy.

KW - Localisation

KW - Perceptual inference

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 181

BT - Biomimetic and Biohybrid Systems

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A2 - Vouloutsi, Vasiliki

A2 - Moses, Kenneth

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Craig P, Aitchison L , Lepora NF. Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method. In Hunt A, Vouloutsi V, Moses K, Quinn R, Mura A, Prescott T, Verschure PF, editors, Biomimetic and Biohybrid Systems : 11th International Conference, Living Machines 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 169-181. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-20470-8_18

Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method

Abstract

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Bibliographical note

Keywords

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Active Inference for Tactile Sensor Control

Cite this

Active Inference for Artificial Touch: A Biologically-Plausible Tactile Control Method

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Handle.net

Other files and links

Fingerprint

Student theses

Active Inference for Tactile Sensor Control

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