Object Classification Utilizing Neuromorphic Proprioceptive Signals in Active Exploration: Validated on a Soft Anthropomorphic Hand Article Swipe
Fengyi Wang
,
Hyeonggeun Yu
,
Nitish V. Thakor
,
Gordon Cheng
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/biorob60516.2024.10719855
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/biorob60516.2024.10719855
Proprioception, a key sensory modality in haptic perception, plays a vital role in perceiving the 3D structure of objects by providing feedback on the position and movement of body parts. The restoration of proprioceptive sensation is crucial for enabling in-hand manipulation and natural control in the prosthetic hand. Despite its importance, proprioceptive sensation is relatively unexplored in an artificial system. In this work, we introduce a novel platform that integrates a soft anthropomorphic robot hand (QB SoftHand) with flexible proprioceptive sensors and a classifier that utilizes a hybrid spiking neural network with different types of spiking neurons to interpret neuromorphic proprioceptive signals encoded by a biological muscle spindle model. The encoding scheme and the classifier are implemented and tested on the datasets we collected in the active exploration of ten objects from the YCB benchmark. Our results indicate that the classifier achieves more accurate inferences than existing learning approaches, especially in the early stage of the exploration. This system holds the potential for development in the areas of haptic feedback and neural prosthetics.
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- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.1109/biorob60516.2024.10719855
- OA Status
- green
- Cited By
- 1
- References
- 25
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- OpenAlex ID
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https://openalex.org/W4403677799Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/biorob60516.2024.10719855Digital Object Identifier
- Title
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Object Classification Utilizing Neuromorphic Proprioceptive Signals in Active Exploration: Validated on a Soft Anthropomorphic HandWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-01Full publication date if available
- Authors
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Fengyi Wang, Hyeonggeun Yu, Nitish V. Thakor, Gordon ChengList of authors in order
- Landing page
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https://doi.org/10.1109/biorob60516.2024.10719855Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2505.17738Direct OA link when available
- Concepts
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Neuromorphic engineering, Computer science, Artificial intelligence, Object (grammar), Soft computing, Computer vision, Proprioception, Soft robotics, Artificial neural network, Physical medicine and rehabilitation, Robot, MedicineTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.muscle | 106 |
| abstract_inverted_index.neural | 89, 171 |
| abstract_inverted_index.parts. | 29 |
| abstract_inverted_index.scheme | 111 |
| abstract_inverted_index.system | 158 |
| abstract_inverted_index.tested | 118 |
| abstract_inverted_index.Despite | 48 |
| abstract_inverted_index.control | 43 |
| abstract_inverted_index.crucial | 36 |
| abstract_inverted_index.encoded | 102 |
| abstract_inverted_index.in-hand | 39 |
| abstract_inverted_index.natural | 42 |
| abstract_inverted_index.network | 90 |
| abstract_inverted_index.neurons | 96 |
| abstract_inverted_index.objects | 18, 130 |
| abstract_inverted_index.results | 136 |
| abstract_inverted_index.sensors | 80 |
| abstract_inverted_index.sensory | 3 |
| abstract_inverted_index.signals | 101 |
| abstract_inverted_index.spiking | 88, 95 |
| abstract_inverted_index.spindle | 107 |
| abstract_inverted_index.system. | 59 |
| abstract_inverted_index.accurate | 143 |
| abstract_inverted_index.achieves | 141 |
| abstract_inverted_index.datasets | 121 |
| abstract_inverted_index.enabling | 38 |
| abstract_inverted_index.encoding | 110 |
| abstract_inverted_index.existing | 146 |
| abstract_inverted_index.feedback | 21, 169 |
| abstract_inverted_index.flexible | 78 |
| abstract_inverted_index.indicate | 137 |
| abstract_inverted_index.learning | 147 |
| abstract_inverted_index.modality | 4 |
| abstract_inverted_index.movement | 26 |
| abstract_inverted_index.platform | 67 |
| abstract_inverted_index.position | 24 |
| abstract_inverted_index.utilizes | 85 |
| abstract_inverted_index.SoftHand) | 76 |
| abstract_inverted_index.collected | 123 |
| abstract_inverted_index.different | 92 |
| abstract_inverted_index.interpret | 98 |
| abstract_inverted_index.introduce | 64 |
| abstract_inverted_index.potential | 161 |
| abstract_inverted_index.providing | 20 |
| abstract_inverted_index.sensation | 34, 52 |
| abstract_inverted_index.structure | 16 |
| abstract_inverted_index.artificial | 58 |
| abstract_inverted_index.benchmark. | 134 |
| abstract_inverted_index.biological | 105 |
| abstract_inverted_index.classifier | 83, 114, 140 |
| abstract_inverted_index.especially | 149 |
| abstract_inverted_index.inferences | 144 |
| abstract_inverted_index.integrates | 69 |
| abstract_inverted_index.perceiving | 13 |
| abstract_inverted_index.prosthetic | 46 |
| abstract_inverted_index.relatively | 54 |
| abstract_inverted_index.unexplored | 55 |
| abstract_inverted_index.approaches, | 148 |
| abstract_inverted_index.development | 163 |
| abstract_inverted_index.exploration | 127 |
| abstract_inverted_index.implemented | 116 |
| abstract_inverted_index.importance, | 50 |
| abstract_inverted_index.perception, | 7 |
| abstract_inverted_index.restoration | 31 |
| abstract_inverted_index.exploration. | 156 |
| abstract_inverted_index.manipulation | 40 |
| abstract_inverted_index.neuromorphic | 99 |
| abstract_inverted_index.prosthetics. | 172 |
| abstract_inverted_index.proprioceptive | 33, 51, 79, 100 |
| abstract_inverted_index.Proprioception, | 0 |
| abstract_inverted_index.anthropomorphic | 72 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.65336834 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |