A Real-Time Planning and Control Framework for Robust and Dynamic Quadrupedal Locomotion

被引:4
作者
Li, Jun [1 ,2 ]
Gao, Haibo [1 ]
Wan, Yuhui [2 ]
Yu, Haitao [1 ]
Zhou, Chengxu [2 ]
机构
[1] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150001, Peoples R China
[2] Univ Leeds, Sch Mech Engn, Leeds LS2 9JT, W Yorkshire, England
基金
英国工程与自然科学研究理事会; “创新英国”项目; 中国国家自然科学基金;
关键词
Bionic robot; Legged locomotion; Motion planning; Whole-body control; OPTIMIZATION;
D O I
10.1007/s42235-023-00347-9
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Legged locomotion poses significant challenges due to its nonlinear, underactuated and hybrid dynamic properties. These challenges are exacerbated by the high-speed motion and presence of aerial phases in dynamic legged locomotion, which highlights the requirement for online planning based on current states to cope with uncertainty and disturbances. This article proposes a real-time planning and control framework integrating motion planning and whole-body control. In the framework, the designed motion planner allows a wider body rotation range and fast reactive behaviors based on the 3-D single rigid body model. In addition, the combination of a Bezier curve based trajectory interpolator and a heuristic-based foothold planner helps generate continuous and smooth foot trajectories. The developed whole-body controller uses hierarchical quadratic optimization coupled with the full system dynamics, which ensures tasks are prioritized based on importance and joint commands are physically feasible. The performance of the framework is successfully validated in experiments with a torque-controlled quadrupedal robot for generating dynamic motions.
引用
收藏
页码:1449 / 1466
页数:18
相关论文
共 41 条
  • [1] Bhat SP, 1998, P AMER CONTR CONF, P2785, DOI 10.1109/ACC.1998.688361
  • [2] Bledt G, 2020, IEEE INT CONF ROBOT, P406, DOI [10.1109/icra40945.2020.9197488, 10.1109/ICRA40945.2020.9197488]
  • [3] Bledt G, 2017, IEEE INT C INT ROBOT, P4102, DOI 10.1109/IROS.2017.8206268
  • [4] Bloesch M., 2012, P ROBOTICS SCI SYSTE
  • [5] Budhiraja R, 2019, IEEE INT CONF ROBOT, P6727, DOI [10.1109/icra.2019.8793878, 10.1109/ICRA.2019.8793878]
  • [6] Carpentier J, 2019, IEEE/SICE I S SYS IN, P614, DOI 10.1109/SII.2019.8700380
  • [7] Chengxu Zhou, 2016, 2016 IEEE International Conference on Automation Science and Engineering (CASE), P1026, DOI 10.1109/COASE.2016.7743516
  • [8] The MIT Humanoid Robot: Design, Motion Planning, and Control For Acrobatic Behaviors
    Chignoli, Matthew
    Kim, Donghyun
    Stanger-Jones, Elijah
    Kim, Sangbae
    [J]. PROCEEDINGS OF THE 2020 IEEE-RAS 20TH INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS 2020), 2021, : 1 - 8
  • [9] Dynamic Complementarity Conditions and Whole-Body Trajectory Optimization for Humanoid Robot Locomotion
    Dafarra, Stefano
    Romualdi, Giulio
    Pucci, Daniele
    [J]. IEEE TRANSACTIONS ON ROBOTICS, 2022, 38 (06) : 3414 - 3433
  • [10] Di Carlo J, 2018, IEEE INT C INT ROBOT, P7440, DOI 10.1109/IROS.2018.8594448