Understanding human motor control for complex movements during assistance and its application
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1.Intention Prediction and Joint Action Performance in Asymmetrical Relationships
- 关键词:
- Human engineering;Human robot interaction;Microrobots;Action performance;Assistive robots;Gain insight;Human Interface;Human robots;Human users;Human-machine systems;Intention predictions;Joint actions;Users strength
- Eshita, Hayato;Yeoh, Wen Liang;Yamaguchi, Nobuhiko;Okumura, Hiroshi;Fukuda, Osamu
- 《2024 SICE Festival with Annual Conference, SICE FES 2024》
- 2024年
- August 27, 2024 - August 30, 2024
- Kochi City, Japan
- 会议
As technology develops and robots gradually become a part of everyday life, devices that provide physical assistance to humans will become increasingly common. Such robots must often physically interact with the user for extended periods of time and must provide auxiliary forces that complement the user's strength to accomplish certain goals. This requires close cooperation and close coordination between the human user and the assistive robot. The purpose of this study is to understand how two humans cooperate and coordinate in order to gain insight into how to improve human-robot coordination. In this study, a tracking task involving a pair of humans was conducted. The task used 'predictable' and 'unpredictable' sine waves. In the experiment, the roles of the two humans were divided into a 'user' focusing on the experimental task and an 'assistant' focusing on support, and the amount of information given to the 'assistant' was divided into three levels ('Full knowledge', 'Short-term knowledge', and 'No knowledge') to try to understand the coordination and cooperation tendencies of the two humans. The experimental results showed that in some conditions, the rate of increase in error and load decreased as the amount of task knowledge given to the 'assistant' increased, compared to when the task was performed 'solo'. © 2024 The Society of Instrument and Control Engineers - SICE.
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