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Falling Prediction based on Machine Learning for Biped Robots

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Abstract

Biped robots are expected to be able to work in complex environments. However, these robots will inevitably fall at times and such falls may cause injury to the robot itself or to people nearby. Therefore, it is necessary to detect that the robot is falling to be able to warn the robot in sufficient time when it is about to fall and to switch its controller to protect the vulnerable parts of the robot. Modeling and analysis of the biped robot falling problem cannot be fully accurate and many current learning-based methods rely on large quantities of fall data that are difficult to use to train fragile robots. A machine learning-based fall detection method is therefore proposed in this paper. This method requires only a small amount of training data to obtain good fall detection, making the training process on the robot platform much safer. A support vector machine is used to determine the state of the robot and the decision boundary of the stable state is updated during motion to enable the classifier to match the motion capability of the robot.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 91748202, 61973039, and 3192029.

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 91748202, 62073041, and Beijing Natural Science Foundation under Grant 3192029.

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Authors and Affiliations

  1. Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, 100081, China

    Tong Wu, Zhangguo Yu, Xuechao Chen, Chencheng Dong, Zhifa Gao & Qiang Huang

  2. Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing, 100081, China

    Zhangguo Yu, Xuechao Chen & Qiang Huang

Authors
  1. Tong Wu
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  2. Zhangguo Yu
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  3. Xuechao Chen
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  4. Chencheng Dong
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  5. Zhifa Gao
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  6. Qiang Huang
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Contributions

Tong Wu: Conceived and designed the experiments. Xuechao Chen: Contributed to the conception of the study. Zhangguo Yu: Contributed significantly to analysis and manuscript preparation. Chencheng Dong: Helped perform the analysis with constructive discussions. Zhifa Gao: Performed the data analyses. Qiang Huang: helped perform the analysis with constructive discussions.

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Correspondence to Zhangguo Yu.

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Wu, T., Yu, Z., Chen, X. et al. Falling Prediction based on Machine Learning for Biped Robots. J Intell Robot Syst 103, 68 (2021). https://doi.org/10.1007/s10846-021-01506-y

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