Chao Ding, Lelai Zhou, Xuewen Rong, Yibin Li, and Jason Gu


  1. [1] G. Bledt, M.J. Powell, B. Katz, et al., MIT Cheetah 3: Design and control of a robust, dynamic quadruped robot, 2018 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), IEEE, Madrid, Spain, 2018, 2245–2252.
  2. [2] Nelson G, Saunders A, Playter R, The PETMAN and Atlas robots at Boston dynamics, Humanoid Robotics: A Reference Springer, 2019, 169–186.
  3. [3] S. Kuindersma, R. Deits, M. Fallon, et al., Optimizationbased locomotion planning, estimation, and control design for the Atlas humanoid robot, Autonomous Robots, 40 (3), 2016, 429–455.
  4. [4] M. Hutter, C. Gehring, M. Bloesch, et al., StarlETH: A compliant quadrupedal robot for fast, efficient, and versatile locomotion, Adaptive Mobile Robotics, (Baltimore, USA: World Scientific Publishing Co. Pt. Ltd.), 23–26 July, 2012, 483–490. ISBN: 978-981-4415-94-1.
  5. [5] M. Hutter, C. Gehring, A. Lauber, et al., ANYmal—Toward legged robots for harsh environments, Advanced Robotics, 31(17), 2017, 918–931.
  6. [6] C. Semini, N.G. Tsagarakis, E. Guglielmino, et al., Design of HyQ—A hydraulically and electrically actuated quadruped robot, Proceedings of the Institution of Mechanical Engineers I, 225(6), 2011, 831–849.
  7. [7] C. Semini, V. Barasuol, J. Goldsmith, et al. Design of the hydraulically actuated, torque-controlled quadruped robot hyq2max, IEEE/ASME Transactions on Mechatronics, 22(2), 2017, 635–646.
  8. [8] J. Di Carlo, P.M. Wensing, B. Katz, et al., Dynamic locomotion in the MIT Cheetah 3 through convex model-predictive control, 2018 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), IEEE, Madrid, Spain, 2018, 1–9.
  9. [9] J. Hwangbo, J. Lee, A. Dosovitskiy, et al., Learning agile and dynamic motor skills for legged robots, Science Robotics, 4(26), 2019, eaau5872.
  10. [10] V. Barasuol, J. Buchli, C. Semini, et al., A reactive controller framework for quadrupedal locomotion on challenging terrain, 2013 IEEE Int. Conf. on Robotics and Automation, IEEE, Karlsruhe, Germany, 2013, 2554–2561.
  11. [11] M. Khorram and S.A.A. Moosavian, Balance recovery of a quadruped robot, RSI Int. Conf. on Robotics and Mechatronics, IEEE, Tehran, Iran, 2015, 259–264.
  12. [12] Y. Zhu and B. Jin, Compliance control of a legged robot based on improved adaptive control: Method and experiments, International Journal of Robotics and Automation, 31(5), 2016, 366–373.
  13. [13] T. Koolen, T. De Boer, J. Rebula, et al., Capturability-based analysis and control of legged locomotion, Part 1: Theory and application to three simple gait models, International Journal of Robotics Research, 31(9), 2012, 1094–1113.
  14. [14] J. Pratt, J. Carff, S. Drakunov, et al., Capture point: A step toward humanoid push recovery, IEEE-RAS Int. Conf. on Humanoid Robots, IEEE, Genova, Italy, 2006, 200–207.
  15. [15] M. Buehler, R. Playter, and M. Raibert, Robots step outside, Int. Symp. Adaptive Motion of Animals and Machines (AMAM), Ilmenau, 2005, 1–4.
  16. [16] M.H. Raibert and E.R. Tello, Legged Robots That Balance (Cambridge, MA: MIT Press, 1986).
  17. [17] Q.S. Luo, C.Y. Zhou, J. Yan, et al., CPG-based control scheme for quadruped robot to withstand the lateral impact, Transactions of Beijing Institute of Technology, 35(4), 2015, 384–390.
  18. [18] B. Han, X. Luo, Q. Liu, et al., A control strategy for SLIP-based locomotion under lateral impact in 3D space, 2015 IEEE Int. Conf. on Robotics and Biomimetics (ROBIO), IEEE, Zhuhai, China, 2015, 517–522.
  19. [19] J. Pratt, T. Koolen, T. De Boer, et al., Capturability-based analysis and control of legged locomotion, Part 2: Application to M2V2, a lower-body humanoid, International Journal of Robotics Research, 31(10), 2012, 1117–1133.
  20. [20] X. Tian, F. Gao, C. Qi, et al., External disturbance identification of a quadruped robot with parallel–serial leg structure, International Journal of Mechanics & Materials in Design, 12(1), 2016, 109–120.
  21. [21] N. Dini, V.J. Majd, F. Edrisi, et al., Estimation of external forces acting on the legs of a quadruped robot using two nonlinear disturbance observers, IEEE Int. Conf. on Robotics and Mechatronics, Hong Kong, China, 2017, 72–77. 207
  22. [22] Z. Chen, Y.J. Pan, and J. Gu, Adaptive robust control of bilateral teleoperation systems with unmeasurable environmental force and arbitrary time delays, IET Control Theory & Applications, 8(15), 2014, 1456–1464.
  23. [23] Z. Sun, G.S. Yang, B. Zhang, et al., On the concept of the resilient machine, 2011 6th IEEE Conf. on Industrial Electronics and Applications, IEEE, Beijing, China, 2011, 357–360.
  24. [24] T. Zhang, W. Zhang, and M.M. Gupta, An underactuated self-reconfigurable robot and the reconfiguration evolution, Mechanism and Machine Theory, 124, 2018, 248–258.
  25. [25] X. Lai, H. Chen, Y. Wang, et al., Trajectory tracking control with specified posture for planar four-link real underactuated manipulator, International Journal of Robotics and Automation, 34(2), 2019, 194–202.
  26. [26] A. Zhang, J. She, J. Qiu, et al., Inverse motion method for the stabilization of underactuated inertia wheel pendulum, International Journal of Robotics and Automation, 34(3), 2019, 243–252.
  27. [27] H. Chai, J. Meng, X. Rong, et al., Design and implementation of Scalf: An advanced hydraulic quadruped robot, Robot, 36 (4), 2014, 385–391.
  28. [28] M. Raibert, M. Chepponis, and H. Brown, Running on four legs as though they were one, IEEE Journal on Robotics and Automation, 2 (2), 1986, 70–82.
  29. [29] J. Pratt, C.M. Chew, A. Torres, et al. Virtual model control: An intuitive approach for bipedal locomotion, International Journal of Robotics Research, 20(2), 2001, 129–143.
  30. [30] W.J. Zhang and Y. Lin, On the principle of design of re-silient systems–application to enterprise information systems, Enterprise Information Systems, 4(2), 2010, 99–110.

Important Links:

Go Back