Abstract
Recognition of human motion intention plays an important role in many robotic applications, such as human-assistive exoskeletons and rehabilitation robots. Motion intention recognition (MIR) based on physiological signals is one of the most common and intuitive methods. However, physiological signals are sensitive to environmental disturbances and suffer from complex preparation. In this paper, we proposed a novel air bladder-based MIR method, in which the human-robot interaction (HRI) force is measured directly by four air bladders. The air bladders can be installed at the end of a robot to interact with the user’s arm. We validate the linearity and repeatability of the air bladders through comprehensive experiments. In addition, we compare the performance of the proposed air bladder-based MIR method with the conventional method based on force sensors and surface electromyography (sEMG) signals. Experiments show that the proposed method can capture the change of the external force, even when the force changes rapidly. Moreover, the performance of our method is more comparative and robust in caparison with the sEMG-based MIR method.
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Acknowledgements
This work was supported in part by the National Natural Science Foundation of China (Grant No. 52075177), Joint Fund of the Ministry of Education for Equipment Pre-Research (Grant No. 6141A02033124), Research Foundation of Guangdong Province (Grant No. 2019A050505001 and 2018KZDXM002), Guangzhou Research Foundation (Grant No. 202002030324 and 201903010028), Zhongshan Research Foundation (Grant No.2020B2020), and Shenzhen Institute of Artificial Intelligence and Robotics for Society (Grant No. AC01202005011).
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Wu, W., Lin, C., Lin, G., Cai, S., Xie, L. (2021). Motion Intention Recognition Based on Air Bladders. In: Li, H., et al. Social Robotics. ICSR 2021. Lecture Notes in Computer Science(), vol 13086. Springer, Cham. https://doi.org/10.1007/978-3-030-90525-5_51
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DOI: https://doi.org/10.1007/978-3-030-90525-5_51
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