四足机器人动步态下实时足底力优化方法的设计与验证
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摘要
为实现四足机器人在动步态下的稳定行走及最优足底力分配,提出了融合全尺寸虚拟模型和动力学模型的四足机器人控制框架.在支撑相中,将躯干质心虚拟力与足底力分配问题转化成二次型优化问题,通过Gurobi库求最优值,实现实时的最优足底力分配.在摆动相中,融合动力学前馈和虚拟模型控制方法实现了平滑的轨迹追踪.通过Webots动力学仿真,将该方法与基本的位置阻抗控制方法在四足机器人平台上进行了对比分析,结果证明该方法能减小大约30%的足地交互冲击力,同时有效提高了机器人在运动中的稳定性.
In order to achieve the stable walking and optimal feet forces distribution for quadruped robots in a dynamic gait, a control framework based on the fusion of the full-scale virtual model and the dynamic model is proposed. The distribution of the virtual forces at the torso center and the feet forces in the support phase is transformed into a quadratic optimization problem. The optimal distribution of feet forces is achieved in real time through Gurobi library. The dynamical feedforward and the virtual model control methods are integrated in the swing phase to achieve smooth trajectory tracking.Through dynamic simulation software Webots, the method is compared with the basic position impedance control method on the quadruped robot platform. The results show that the method can reduce the impact force by about 30% in the ground interaction, and the stability of the robot movement is effectively improved.
In order to achieve the stable walking and optimal feet forces distribution for quadruped robots in a dynamic gait, a control framework based on the fusion of the full-scale virtual model and the dynamic model is proposed. The distribution of the virtual forces at the torso center and the feet forces in the support phase is transformed into a quadratic optimization problem. The optimal distribution of feet forces is achieved in real time through Gurobi library. The dynamical feedforward and the virtual model control methods are integrated in the swing phase to achieve smooth trajectory tracking.Through dynamic simulation software Webots, the method is compared with the basic position impedance control method on the quadruped robot platform. The results show that the method can reduce the impact force by about 30% in the ground interaction, and the stability of the robot movement is effectively improved.
引文
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[19] Zhang G T, Rong X W, Hui C, et al. Torso motion control and toe trajectory generation of a trotting quadruped robot based on virtual model control[J]. Advanced Robotics, 2016, 30(4):284-297.
[20]鄂明成,刘虎,张秀丽,等.一种粗糙地形下四足仿生机器人的柔顺步态生成方法[J].机器人,2014,36(5):584-591.E M C, Liu H, Zhang X L, et al. Compliant gait generation for a quadruped bionic robot walking on rough terrains[J]. Robot,2014, 36(5):584-591.
[2] Zhang G T, Liu J C, Rong X W, et al. Design of trotting controller for the position-controlled quadruped robot[J]. High Technology Letters, 2016, 22(3):321-333.
[3] Murphy M P, Stephens B, Abe Y, et al. High degree-of-freedom dynamic manipulation[M]//Proceedings of SPIE, Vol.8387.Bellingham, USA:SPIE, 2012. DOI:10.1117/12.919939.
[4] Raibert M. BigDog, the rough-terrain quadruped robot[J]. IFAC Proceedings Volumes, 2008, 17(1). DOI:10.3182/20080706-5-KR-1001.4278.
[5] Boaventura T, Buchli J, Semini C, et al. Model-based hydraulic impedance control for dynamic robots[J]. IEEE Transactions on Robotics, 2015, 31(6):1324-1336.
[6] Winkler A W, Mastalli C, Havoutis I, et al. Planning and execution of dynamic whole-body locomotion for a hydraulic quadruped on challenging terrain[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA:IEEE,2015:5148-5154.
[7] Gehring C, Coros S, Hutter M, et al. Control of dynamic gaits for a quadrupedal robot[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA:IEEE, 2013:3287-3292.
[8] Bellicoso C D, Gehring C, Hwangbo J, et al. Perception-less terrain adaptation through whole body control and hierarchical optimization[C]//16th IEEE-RAS International Conference on Humanoid Robots. Piscataway, USA:IEEE, 2016:558-564.
[9] Zhang T H, An H L, Ma H X. Joint torque and velocity optimization for a redundant leg of quadruped robot[J]. International Journal of Advanced Robotic Systems, 2017, 14(5). DOI:10.1177/1729881417731897.
[10] Lang L, Wang J, Wei Q, et al. Compliant landing of a trotting quadruped robot based on hybrid motion/force robust control[J].Journal of Central South University, 2016, 23(8):1970-1980.
[11]李满天,蒋振宇,郭伟,等.四足仿生机器人单腿系统[J].机器人,2014,36(1):21-28.Li M T, Jiang Z Y, Guo W, et al. Leg Prototype of a bio-inspired quadruped robot[J]. Robot, 2014, 36(1):21-28
[12]蒋振宇.基于SLIP模型的四足机器人对角小跑步态控制研究[D].哈尔滨:哈尔滨工业大学,2014.Jiang Z Y. Control of quadruped robot in trotting gait based on SLIP model[D]. Harbin:Harbin Institute of Technology, 2014.
[13]柯贤锋,王军政,何玉东,等.基于力反馈的液压足式机器人主/被动柔顺性控制[J].机械工程学报,2017,53(1):13-20.Ke X F, Wang J Z, He Y D, et al. Active/passive compliance control for a hydraulic quadruped robot based on force feedback[J]. Journal of Mechanical Engineering, 2017, 53(1):13-20.
[14] Coros S, Karpathy A, Jones B, et al. Locomotion skills for simulated quadrupeds[J]. ACM Transactions on Graphics, 2011,30(4). DOI:10.1145/1964921.1964954.
[15] Valle C M C O, Tanscheit R, Forero Mendoza L A. Computedtorque control of a simulated bipedal robot with locomotion by reinforcement learning[C]//3rd IEEE Latin American Conference on Computational Intelligence. Piscataway, USA:IEEE,2016.
[16] Peng X B, van de Panne M. Learning locomotion skills using deepRL:Does the choice of action space matter?[C]//Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation. New York, USA:ACM, 2017. DOI:10.1145/3099564.3099567.
[17] Merel J, Tassa Y, Srinivasan S, et al. Learning human behaviors from motion capture by adversarial imitation[EB/OL].(2017-07-10)[2018-07-01]. https://arxiv. org/pdf/1707.02201.
[18]孟健.复杂地形环境四足机器人运动控制方法研究与实现[D].济南:山东大学,2015.Meng J. Research and implementation on motion control method of quadruped robot on complex terrain and environment[D]. Jinan:Shandong University, 2015.
[19] Zhang G T, Rong X W, Hui C, et al. Torso motion control and toe trajectory generation of a trotting quadruped robot based on virtual model control[J]. Advanced Robotics, 2016, 30(4):284-297.
[20]鄂明成,刘虎,张秀丽,等.一种粗糙地形下四足仿生机器人的柔顺步态生成方法[J].机器人,2014,36(5):584-591.E M C, Liu H, Zhang X L, et al. Compliant gait generation for a quadruped bionic robot walking on rough terrains[J]. Robot,2014, 36(5):584-591.