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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.05832 |
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| _version_ | 1866916728716394496 |
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| author | Zhou, Songchen Armstrong, Mark Barbareschi, Giulia Ajioka, Toshihiro Hu, Zheng Ando, Ryoichi Yoshifuji, Kentaro Muto, Masatane Minamizawa, Kouta |
| author_facet | Zhou, Songchen Armstrong, Mark Barbareschi, Giulia Ajioka, Toshihiro Hu, Zheng Ando, Ryoichi Yoshifuji, Kentaro Muto, Masatane Minamizawa, Kouta |
| contents | Individuals with upper limb movement limitations face challenges in interacting with others. Although robotic arms are currently used primarily for functional tasks, there is considerable potential to explore ways to enhance users' body language capabilities during social interactions. This paper introduces an Augmented Body Communicator system that integrates robotic arms and a large language model. Through the incorporation of kinetic memory, disabled users and their supporters can collaboratively design actions for the robot arm. The LLM system then provides suggestions on the most suitable action based on contextual cues during interactions. The system underwent thorough user testing with six participants who have conditions affecting upper limb mobility. Results indicate that the system improves users' ability to express themselves. Based on our findings, we offer recommendations for developing robotic arms that support disabled individuals with body language capabilities and functional tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_05832 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Augmented Body Communicator: Enhancing daily body expression for people with upper limb limitations through LLM and a robotic arm Zhou, Songchen Armstrong, Mark Barbareschi, Giulia Ajioka, Toshihiro Hu, Zheng Ando, Ryoichi Yoshifuji, Kentaro Muto, Masatane Minamizawa, Kouta Human-Computer Interaction Robotics Individuals with upper limb movement limitations face challenges in interacting with others. Although robotic arms are currently used primarily for functional tasks, there is considerable potential to explore ways to enhance users' body language capabilities during social interactions. This paper introduces an Augmented Body Communicator system that integrates robotic arms and a large language model. Through the incorporation of kinetic memory, disabled users and their supporters can collaboratively design actions for the robot arm. The LLM system then provides suggestions on the most suitable action based on contextual cues during interactions. The system underwent thorough user testing with six participants who have conditions affecting upper limb mobility. Results indicate that the system improves users' ability to express themselves. Based on our findings, we offer recommendations for developing robotic arms that support disabled individuals with body language capabilities and functional tasks. |
| title | Augmented Body Communicator: Enhancing daily body expression for people with upper limb limitations through LLM and a robotic arm |
| topic | Human-Computer Interaction Robotics |
| url | https://arxiv.org/abs/2505.05832 |