Full Text:   <846>

Summary:  <178>

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On-line Access: 2023-06-12

Received: 2022-06-14

Revision Accepted: 2022-11-28

Crosschecked: 2023-06-12

Cited: 0

Clicked: 778

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yangyang HAN

https://orcid.org/0000-0003-1080-9498

Zhenyu LU

https://orcid.org/0000-0001-7784-5149

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Journal of Zhejiang University SCIENCE A 2023 Vol.24 No.6 P.516-530

http://doi.org/10.1631/jzus.A2200310


A stability locomotion-control strategy for quadruped robots with center-of-mass dynamic planning


Author(s):  Yangyang HAN, Guoping LIU, Zhenyu LU, Huaizhi ZONG, Junhui ZHANG, Feifei ZHONG, Liyu GAO

Affiliation(s):  School of Advanced Manufacturing, Nanchang University, Nanchang 330031, China; more

Corresponding email(s):   luzhenyu@ncu.edu.cn

Key Words:  Center-of-mass (CoM) planning, Quadruped robot, Cooperative scheme, Ground reaction forces, Stability margin


Yangyang HAN, Guoping LIU, Zhenyu LU, Huaizhi ZONG, Junhui ZHANG, Feifei ZHONG, Liyu GAO. A stability locomotion-control strategy for quadruped robots with center-of-mass dynamic planning[J]. Journal of Zhejiang University Science A, 2023, 24(6): 516-530.

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author="Yangyang HAN, Guoping LIU, Zhenyu LU, Huaizhi ZONG, Junhui ZHANG, Feifei ZHONG, Liyu GAO",
journal="Journal of Zhejiang University Science A",
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pages="516-530",
year="2023",
publisher="Zhejiang University Press & Springer",
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%A Zhenyu LU
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%A Junhui ZHANG
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A1 - Liyu GAO
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Abstract: 
Locomotion stability is essential for controlling quadruped robots and adapting them to unstructured terrain. We propose a control strategy with center-of-mass (CoM) dynamic planning for the stable locomotion of these robots. The motion trajectories of the swing legs are synchronized with the CoM of the robot. To implement the synchronous control scheme, we adjusted the swing legs to form a support triangle. The strategy is applicable to both static walk gait and dynamic trot gait. In the motion control processes of the robot legs, the distribution of the ground reaction forces is optimized to minimize joint torque and locomotion energy consumption. We also used an improved joint-torque controller with varied controller coefficients in the stance and swing phases. The simulation and experimental results demonstrate that the robot can complete omnidirectional locomotion in both walk and trot gaits. At a given locomotion speed, the stability margins for the robot during walking and trotting were 27.25% and 37.25% higher, respectively, than in the scheme without CoM planning. The control strategy with energy consumption optimization (ECO) reduced the energy consumption of the robot in walk and trot gaits by 11.25% and 13.83%, respectively, from those of the control scheme without ECO.

基于质心动态规划的四足机器人稳定运动控制策略

作者:韩杨杨1,刘国平1,陆振宇1,纵怀志2,张军辉2,钟飞飞1,高立宇1
机构:1南昌大学,先进制造学院,中国南昌,330031;2浙江大学,流体动力与机电系统国家重点实验室,中国杭州,310027
目的:运动稳定性对于四足机器人至关重要,是其适应非结构化地形的前提。为了提高机器人在运动过程中的机体稳定性,文本提出一种基于质心动态规划的四足机器人稳定控制策略。
创新点:1.在期望速度一定的情况下,同时考虑机器人运动的稳定性和能耗两个问题;2.考虑到机器人机身与各条腿之间的运动协调性问题,设计质心移动与摆动相动作的同步配合方案,并对质心进行实时轨迹规划。
方法:1.为了实现同步控制方案,用摆动腿和支撑腿共同构成支撑三角形,并在静步态基础上对小跑步态做出扩展;2.结合机器人腿在站立和摆动阶段受力情况的不同,设计主力矩由优化的足端反力映射和关节比例微分控制器组成的变权重控制策略。
结论:1.仿真和实验结果表明,采用本文提出的控制策略,机器人可以完成行走和小跑两种步态的全向运动;2.在一定的运动速度下,机器人行走和小跑的稳定裕度分别比未进行质心规划的方案提高了27.25%和37.25%;3.与未进行能耗优化控制的方案相比,采用所提策略的机器人的能耗分别降低了11.25%(行走)和13.83%(小跑)。

关键词:质心规划;四足机器人;配合方案;地面反力;稳定裕度

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Reference

[1]ArenaP, PatanèL, SueriP, et al., 2021. A data-driven neural network model predictive steering controller for a bio-inspired quadruped robot. IFAC-PapersOnLine, 54(17):93-98.

[2]BoaventuraT, SeminiC, BuchliJ, et al., 2012. Dynamic torque control of a hydraulic quadruped robot. Proceedings of the IEEE International Conference on Robotics and Automation, p.1889-1894.

[3]ChignoliM, WensingPM, 2020. Variational-based optimal control of underactuated balancing for dynamic quadrupeds. IEEE Access, 8:49785-49797.

[4]di CarloJ, WensingPM, KatzB, et al., 2018. Dynamic locomotion in the MIT Cheetah 3 through convex model-predictive control. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, p.1-9.

[5]DingYR, PandalaA, LiCZ, et al., 2021. Representation-free model predictive control for dynamic motions in quadrupeds. IEEE Transactions on Robotics, 37(4):1154-1171.

[6]DudzikT, ChignoliM, BledtG, et al., 2020. Robust autonomous navigation of a small-scale quadruped robot in real-world environments. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, p.3664-3671.

[7]FocchiM, del PreteA, HavoutisI, et al., 2017. High-slope terrain locomotion for torque-controlled quadruped robots. Autonomous Robots, 41(1):259-272.

[8]FukuiT, FujisawaH, OtakaK, et al., 2019. Autonomous gait transition and galloping over unperceived obstacles of a quadruped robot with CPG modulated by vestibular feedback. Robotics and Autonomous Systems, 111:1-19.

[9]Gonzalez de SantosP, JimenezMA, ArmadaMA, 1998. Dynamic effects in statically stable walking machines. Journal of Intelligent and Robotic Systems, 23(1):71-85.

[10]GonzalezC, BarasuolV, FrigerioM, et al., 2020. Line walking and balancing for legged robots with point feet. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, p.3649-3656.

[11]HaoQ, WangZB, WangJZ, et al., 2020. Stability-guaranteed and high terrain adaptability static gait for quadruped robots. Sensors, 20(17):4911.

[12]HutterM, GehringC, JudD, et al., 2016. ANYmal–a highly mobile and dynamic quadrupedal robot. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, p.38-44.

[13]HutterM, GehringC, LauberA, et al., 2017. ANYmal–toward legged robots for harsh environments. Advanced Robotics, 31(17):918-931.

[14]HyunDJ, SeokS, LeeJ, et al., 2014. High speed trot-running: implementation of a hierarchical controller using proprioceptive impedance control on the MIT Cheetah. The International Journal of Robotics Research, 33(11):1417-1445.

[15]LeeC, AnD, 2021. Reinforcement learning and neural network-based artificial intelligence control algorithm for self-balancing quadruped robot. Journal of Mechanical Science and Technology, 35(1):307-322.

[16]LinPC, KomsuogluH, KoditschekDE, 2005. A leg configuration measurement system for full-body pose estimates in a hexapod robot. IEEE Transactions on Robotics, 21(3):411-422.

[17]LiuLQ, ZhangCR, 2020. Dynamic properties of VDP-CPG model in rhythmic movement with delay. Mathematical Biosciences and Engineering, 17(4):3190-3202.

[18]McClainEW, MeekS, 2018. Determining optimal gait parameters for a statically stable walking human assistive quadruped robot. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, p.‍1751-1756.

[19]ParkHW, WensingPM, KimS, 2017. High-speed bounding with the MIT Cheetah 2: control design and experiments. The International Journal of Robotics Research, 36(2):167-192.

[20]PepeG, LaurenzaM, BelfioreNP, et al., 2021. Quadrupedal robots’ gaits identification via contact forces optimization. Applied Sciences, 11(5):2102.

[21]RaibertMH, 1986. Legged Robots That Balance. MIT Press, Cambridge, USA, p.44-56.

[22]ShaoYC, JinYB, LiuXW, et al., 2022. Learning free gait transition for quadruped robots via phase-guided controller. IEEE Robotics and Automation Letters, 7(2):1230-1237.

[23]SrinivasT, MadhusudhanAKK, ManoharL, et al., 2021. Valkyrie-design and development of gaits for quadruped robot using particle swarm optimization. Applied Sciences, 11(16):7458.

[24]TianJ, MaC, WeiC, et al., 2019. A smooth gait planning framework for quadruped robot based on virtual model control. Proceedings of the 12th International Conference on Intelligent Robotics and Applications, p.398-410.

[25]WangYQ, YeLQ, WangXQ, et al., 2020. A static gait generation for quadruped robots with optimized walking speed. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, p.1899-1906.

[26]YeomH, BaeJ, 2021. A dynamic gait stabilization algorithm for quadrupedal locomotion through contact time modulation. Nonlinear Dynamics, 104(3):2275-2289.

[27]ZhangML, ZhangYJ, HeXL, et al., 2021. Adaptive pid control and its application based on a double-layer BP neural network. Processes, 9(8):1475.

[28]ZhangSS, LiuM, YinYF, et al., 2019. Static gait planning method for quadruped robot walking on unknown rough terrain. IEEE Access, 7:177651-177660.

[29]ZhangY, WangH, DingY, et al., 2021. Adaptive walking control for a quadruped robot on irregular terrain using the complex-valued CPG network. Symmetry, 13(11):2090.

[30]ZhouLL, LiTF, LiuZY, et al., 2021. An efficient gait-generating method for electrical quadruped robot based on humanoid power planning approach. Journal of Bionic Engineering, 18(6):1463-1474.

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