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Planning and Execution of Dynamic Whole-body Locomotion for a Wheeled Biped Robot on Uneven Terrain

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  • Robot and Applications
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Abstract

To improve the adaptability of the wheeled biped robot (WBR) to uneven terrain, firstly an integrated modeling method for wheeled-legs is proposed. The under-actuated part is effectively restrained by defining the interaction force between the WBR and the trunk. The mapping relationship between the wheeled leg’s end force and the joint torques in the balanced state is built. Based on this premise, a control framework that does not rely on external sensors is proposed, and the trunk pose is used as the task space to plan the generalized force output of the wheeled legs and calculate the joint torques. Since the joint space position is not constrained, the leg wheels will be based on the terrain conditions and are adaptively stretched and adjusted back and forth. To further improve the terrain adaptability, a slope estimator and a stabilizer are constructed to deal with the attitude fluctuation caused by the sudden change of terrain. The control framework is proved to verify by simulations and experiment.

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References

  1. Boston Dynamics. Handle robot reimagined for logistics. Youtube, 2019. [Online]. Available: https://youtu.be/5iV_hB08Uns.

  2. L. Zhao, Z. Yu, X. Chen, G. Huang, W. Wang, L. Han, X. Qiu, X. Zhang, and Q. Huang, “System design and balance control of a novel electrically-driven wheel-legged humanoid robot,” Proc. of IEEE International Conference on Unmanned Systems (ICUS), pp. 742–747, 2021.

  3. X. Li, H. Zhou, S. Zhang, H. Feng, and Y. Fu, “WLR-II, a hose-less hydraulic wheel-legged robot,” Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4339–4346, 2019.

  4. V. Klemm, A. Morra, C. Salzmann, F. Tschopp, K. Bodie, L. Gulich, N. Kung, D. Mannhart, C. Pfister, M. Vierneisel, F. Weber, R. Deuber, and R. Siegwart, “Ascento: A two-wheeled jumping robot,” Proc. of International Conference on Robotics and Automation, pp. 7515–7521, 2019.

  5. X. Ruan and J. Cai, “Fuzzy backstepping controllers for two-wheeled self balancing robot,” Proc. of International Asia Vonference on Informatics in Control, Automation and Robotics (CAR 09), pp. 166–169, 2009.

  6. S. Kim, J. Seo, and S. Kwon, “Development of a two-wheeled mobile tilting and balancing (MTB) robot,” Proc. of 11th International Conference on Control, Automation and Systems (ICCAS), pp. 1–6, 2011.

  7. F. Grasser, A. D’arrigo, S. Colombi, and A. Ruffer, “JOE: A mobile, inverted pendulum,” IEEE Transactions on Industrial Electronics, vol. 49, no. 1, pp. 107–114, 2002.

    Article  Google Scholar 

  8. M. Vukobratovíc and B. Borovac, “Zero-moment point — Thirty five years of its life,” International Journal of Humanoid Robotics, vol. 1, no. 1, pp. 157–173, 2004.

    Article  Google Scholar 

  9. F. Dai, X. Gao, S. Jiang, Y. Liu, and J. Li, “A multi-DOF two wheeled inverted pendulum robot climbing on a slope,” Proc. of IEEE International Conference on Robotics and Biomimetics (ROBIO 2014), IEEE, 2015.

  10. V. Klemm, A. Morra, L. Gulich, D. Mannhart, D. Rohr, M. Kamel, Y. de Viragh, and R. Siegwart, “LQR-assisted whole-body control of a wheeled bipedal robot with kinematic loops,” IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 3745–3752, 2020.

    Article  Google Scholar 

  11. S. Xin and S. Vijayakumar, “Online dynamic motion planning and control for wheeled biped robots,” arXiv preprint arXiv:2003.03678, 2020.

  12. H. Zhou, X. Li, H. Feng, J. Li, S. Zhang, and Y. Fu, “Model decoupling and control of the wheeled humanoid robot moving in sagittal plane,” Proc. of 19th International Conference on Humanoid Robots, Toronto, Canada, October 15–17, 2019.

  13. Y. Zhang, L. Zhang, W. Wang, Y. Li, and Q. Zhang, “Design and implementation of a two-wheel and hopping robot with a linkage mechanism,” IEEE Access, vol. 6, pp. 42422–42430, 2018.

    Article  Google Scholar 

  14. H. Chen, B. Wang, Z. Hong, C. Shen, P. Wensing, and W. Zhang, “Underactuated motion planning and control for jumping with wheeled-bipedal robots,” IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 747–754, 2021.

    Article  Google Scholar 

  15. L. Cui, S. Wang, J. Zhang, D. Zhang, J. Lai, Y. Zheng, Z. Zhang, and Z.-P. Jiang, “Learning-based balance control of wheel-legged robots,” IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 7667–7674, 2021.

    Article  Google Scholar 

  16. J. Li, J. Wang, S. Wang, W. Qi, L. Zhang, Y. Hu, and H. Su, “Neural approximation-based model predictive tracking control of nonholonomic wheel-legged robots,” International Journal of Control, Automation, and Systems, vol. 19, no. 1, pp. 372–381, 2021.

    Article  Google Scholar 

  17. T. Chen, X. Sun, Z. Xu, Y. Li, X. Rong, and L. Zhou, “A trot and flying trot control method for quadruped robot based on optimal foot force distribution,” Journal of Bionic Engineering, vol. 16, no. 4, pp. 621–632, 2019.

    Article  Google Scholar 

  18. Y. Lee, S. Hwang, and J. Park, “Balancing of humanoid robot using contact force/moment control by task-oriented whole body control framework,” Autonomous Robots, vol. 40, no. 3, pp. 457–472, 2016.

    Article  Google Scholar 

  19. L. Saab, O. E. Ramos, F. Keith, N. Mansard, P. Soueres, and J. Fourquet, “Dynamic whole-body motion generation under rigid contacts and other unilateral constraints,” IEEE Transactions on Robotics, vol. 29, no. 2, pp. 346–362, April 2013.

    Article  Google Scholar 

  20. D. Kim, J. di Carlo. B. Katz, G. Bledt, and S. Kim, “Highly dynamic quadruped locomotion via whole-body impulse control and model predictive control,” arXiv preprint arXiv: 1909.06586v1, 2019.

  21. X. Chang, H. X. Ma, and H. L. An, “Quadruped robot control through model predictive control with PD compensator,” International Journal of Control, Automation, and Systems, vol. 19, no. 11, pp. 3776–3784, 2021.

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Rail Transportation, Shandong Jiaotong University, Jinan, 250357, China

    Yaxian Xin & Jiuhong Ruan

  2. School of Control Science and Engineering, Shandong University, Jinan, 250061, China

    Yibin Li, Hui Chai & Xuewen Rong

Authors
  1. Yaxian Xin
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  2. Yibin Li
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  3. Hui Chai
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  4. Xuewen Rong
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Corresponding author

Correspondence to Yaxian Xin.

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The authors declared that they have no conflicts of interest to this work.

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This work was supported by National Science Foundation of China(Grant No.62203278, Grant No.62073191, Grant No.61973185, Grant No.61973135, Grant No.91948201) and the National Key Research and Development Program of China under Grant 2017YFB1302102.

Yaxian Xin received her B.S. degree from Qufu Normal University, in 2014 and an M.S. degree from the Qilu University of Technology, in 2017, and a Ph.D. degree from Shandong University in 2021. Her research interests include intelligent control and robotics.

Yibin Li received his B.S. degree from Tianjin University, China, in 1982, an M.S. degree from the Shandong University of Science and Technology, China, in 1988, and a Ph.D. degree from Tianjin University, in 2006. He is currently a Professor at the School of Control Science and Engineering, Shandong University, China. His research interests include robotics, mechatronics, intelligent control, and intelligent vehicles.

Hui Chai received his B.S., M.S., and Ph.D. degrees from Shandong University, China, in 2004, 2007, and 2016, respectively. He is currently an Associate Professor at the School of Control Science and Engineering, Shandong University, China. His research interests include robotics and intelligent control.

Xuewen Rong received his B.S. and M.S. degrees from the Shandong University of Science and Technology, China, in 1996 and 1999, respectively, and a Ph.D. degree from Shandong University, China, in 2013. He is currently a Professor with the School of Control Science and Engineering, Shandong University. His research interests include bionic robotics, mechatronics, hydraulic servo transmission, and control systems.

Jiuhong Ruan received his B.S. degree from North University of China, in 1997 and an M.S. degree from Shandong University of Science and Technology, in 2001, and a Ph.D. degree from Beijing Institute of Technology in 2005. His research interests include advanced control methods, robot technology, autopilot, and rail transit technology.

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Xin, Y., Li, Y., Chai, H. et al. Planning and Execution of Dynamic Whole-body Locomotion for a Wheeled Biped Robot on Uneven Terrain. Int. J. Control Autom. Syst. 22, 1337–1348 (2024). https://doi.org/10.1007/s12555-022-0866-1

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  • DOI: https://doi.org/10.1007/s12555-022-0866-1

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