Neuromorphic touch for robotics—a review
The field of neuromorphic tactile sensing aims to emulate the biological mechanisms of touch to enable artificial systems with efficiency, adaptability, and precision akin to natural tactile perception. Inspired by the spike-based data encoding of biological mechanoreceptors and neural processing, n...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | Neuromorphic Computing and Engineering |
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| Online Access: | https://doi.org/10.1088/2634-4386/adf091 |
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| _version_ | 1849245403049885696 |
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| author | Tianyi Liu George Brayshaw Ao Li Xingchen Xu Benjamin Ward-Cherrier |
| author_facet | Tianyi Liu George Brayshaw Ao Li Xingchen Xu Benjamin Ward-Cherrier |
| author_sort | Tianyi Liu |
| collection | DOAJ |
| description | The field of neuromorphic tactile sensing aims to emulate the biological mechanisms of touch to enable artificial systems with efficiency, adaptability, and precision akin to natural tactile perception. Inspired by the spike-based data encoding of biological mechanoreceptors and neural processing, neuromorphic tactile sensors (NTSs) leverage event-driven architectures to handle sensory information through sparse, low-power, and efficient formats. This review explores the state of neuromorphic tactile sensing, emphasizing its biological foundations, sensor technologies and encoding techniques within the field of robotics. By bridging biological touch mechanisms with neuromorphic engineering, NTSs have the potential to enhance robotic manipulation, prosthetics, and human–machine interfaces. Challenges and future directions include developing novel materials for sensors, improving the performance of spiking neural networks and lowering the barrier to entry into neuromorphic touch research through open-sourcing code and datasets. This review underscores the potential of neuromorphic tactile sensing in creating highly efficient and versatile tactile systems for robotics and beyond. |
| format | Article |
| id | doaj-art-cb850a3a09f0408d9fcdd9be06e2c50d |
| institution | Kabale University |
| issn | 2634-4386 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Neuromorphic Computing and Engineering |
| spelling | doaj-art-cb850a3a09f0408d9fcdd9be06e2c50d2025-08-20T03:58:49ZengIOP PublishingNeuromorphic Computing and Engineering2634-43862025-01-015303200110.1088/2634-4386/adf091Neuromorphic touch for robotics—a reviewTianyi Liu0https://orcid.org/0009-0004-0516-6787George Brayshaw1https://orcid.org/0000-0002-3556-2674Ao Li2https://orcid.org/0009-0002-9084-6116Xingchen Xu3https://orcid.org/0009-0004-9643-8951Benjamin Ward-Cherrier4https://orcid.org/0000-0001-9614-7004University of Bristol , Bristol, United KingdomUniversity of Bristol , Bristol, United KingdomUniversity of Bristol , Bristol, United KingdomUniversity of Bristol , Bristol, United KingdomUniversity of Bristol , Bristol, United KingdomThe field of neuromorphic tactile sensing aims to emulate the biological mechanisms of touch to enable artificial systems with efficiency, adaptability, and precision akin to natural tactile perception. Inspired by the spike-based data encoding of biological mechanoreceptors and neural processing, neuromorphic tactile sensors (NTSs) leverage event-driven architectures to handle sensory information through sparse, low-power, and efficient formats. This review explores the state of neuromorphic tactile sensing, emphasizing its biological foundations, sensor technologies and encoding techniques within the field of robotics. By bridging biological touch mechanisms with neuromorphic engineering, NTSs have the potential to enhance robotic manipulation, prosthetics, and human–machine interfaces. Challenges and future directions include developing novel materials for sensors, improving the performance of spiking neural networks and lowering the barrier to entry into neuromorphic touch research through open-sourcing code and datasets. This review underscores the potential of neuromorphic tactile sensing in creating highly efficient and versatile tactile systems for robotics and beyond.https://doi.org/10.1088/2634-4386/adf091tactile sensingneuromorphicspiking neural networksneurorobotics |
| spellingShingle | Tianyi Liu George Brayshaw Ao Li Xingchen Xu Benjamin Ward-Cherrier Neuromorphic touch for robotics—a review Neuromorphic Computing and Engineering tactile sensing neuromorphic spiking neural networks neurorobotics |
| title | Neuromorphic touch for robotics—a review |
| title_full | Neuromorphic touch for robotics—a review |
| title_fullStr | Neuromorphic touch for robotics—a review |
| title_full_unstemmed | Neuromorphic touch for robotics—a review |
| title_short | Neuromorphic touch for robotics—a review |
| title_sort | neuromorphic touch for robotics a review |
| topic | tactile sensing neuromorphic spiking neural networks neurorobotics |
| url | https://doi.org/10.1088/2634-4386/adf091 |
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