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Hierarchical Trajectory Optimization for Humanoid Robot Jumping Motion

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Intelligent Robotics and Applications (ICIRA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14272))

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Abstract

In order to make the robot have high dynamic motion ability, this paper uses the trajectory optimization method to plan the jumping motion trajectory of the humanoid robot quickly and effectively, and carries out the jumping motion experiment on the HIT-HU humanoid robot platform. In order to improve the solving speed of trajectory optimization problem, simplified centroid dynamics model and single rigid body model are established. Differential dynamic programming (DDP) based on the combination of the centroid dynamic model and the whole body joint kinematic model is used to solve the hopping trajectory optimization problem with high accuracy, and the external penalty function method is used to deal with the relevant constraints. In order to overcome the problem that the solver is sensitive to the initial point selection, a hierarchical trajectory optimization framework is proposed. The framework uses the direct collocation method based on the single rigid body model. The trajectory of the simplified model is used as the initial trajectory guess, and the differential dynamic programming method is introduced to solve the optimal trajectory of the whole joint. The differential dynamic programming algorithm using the direct method of warm start is about twice as fast as the method of manually given initial trajectory. The simulation and experimental verification of the vertical jump trajectories generated by the algorithm on the humanoid robot HIT-HU show that the jump trajectories generated by the algorithm can be effectively transformed into the motion trajectories of humanoid robots, and can be effectively executed on the physical prototype. This further verifies the effectiveness of the algorithm and plays an important role in practical application.

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Acknowledgments

This work was supported by Key Research Project of Zhejiang Lab [No. 115002-AC2101], the Natural Science Foundation of Heilongjiang Province of China [YQ2021F011].

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Authors and Affiliations

  1. Intelligent Robot Research Center, Zhejiang Laboratory, Hangzhou, 311100, China

    Junbao Sun & Yili Fu

  2. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, 150001, China

    Junbao Sun, Haopeng Liu, Xu Li, Haibo Feng, Yili Fu & Songyuan Zhang

Authors
  1. Junbao Sun
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  2. Haopeng Liu
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  3. Xu Li
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  4. Haibo Feng
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  5. Yili Fu
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  6. Songyuan Zhang
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Corresponding author

Correspondence to Yili Fu .

Editor information

Editors and Affiliations

  1. Zhejiang University, Hangzhou, China

    Huayong Yang

  2. Harbin Institute of Technology, Shenzhen, China

    Honghai Liu

  3. Zhejiang University, Hangzhou, China

    Jun Zou

  4. Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

  5. Shenyang Institute of Automation, Shenyang, Liaoning, China

    Lianqing Liu

  6. Zhejiang University, Hangzhou, China

    Geng Yang

  7. Zhejiang University, Hangzhou, China

    Xiaoping Ouyang

  8. Harbin Institute of Technology, Shenzhen, China

    Zhiyong Wang

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sun, J., Liu, H., Li, X., Feng, H., Fu, Y., Zhang, S. (2023). Hierarchical Trajectory Optimization for Humanoid Robot Jumping Motion. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14272. Springer, Singapore. https://doi.org/10.1007/978-981-99-6480-2_3

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  • DOI: https://doi.org/10.1007/978-981-99-6480-2_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-6479-6

  • Online ISBN: 978-981-99-6480-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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