Dynamic Balance and Trajectory Tracking Control of Quadruped Robots Based on Virtual Model Control

As for a motion control framework of robots, virtual model control (VMC) can use virtual components to create virtual forces/torques. Actually, the virtual forces/torques are generated by joint actuators when the virtual components interact between robots and environments. In this paper, a virtual model control is proposed to do the dynamic balance control of quadruped robots in trot gait. In each leg, virtual model control includes swing phase control of robots and stance phase counterparts. In whole body, based on the forces/torques distribution method between two stance legs, virtual model control is mainly about the attitude control containing roll, pitch and yaw. Then, an intuitive approach of velocity control is employed for the locomotion of quadruped robots. Based on the velocity planning and control, a trajectory tracking control approach is investigated by considering four factors: terrain complexity index, curvature radius of given trajectory, distance to terminal, and maximum velocity of quadruped robots. Finally, the effectiveness of proposed controllers is validated by co-simulations.

[1]  Wei Shen,et al.  Energy saving control in separate meter in and separate meter out control system , 2018 .

[2]  Bin Liang,et al.  Locomotion Control for Quadruped Robot Combining Central Pattern Generators with Virtual Model Control , 2019, 2019 IEEE 15th International Conference on Control and Automation (ICCA).

[3]  Darwin G. Caldwell,et al.  A reactive controller framework for quadrupedal locomotion on challenging terrain , 2013, 2013 IEEE International Conference on Robotics and Automation.

[4]  Peter Fankhauser,et al.  ANYmal - a highly mobile and dynamic quadrupedal robot , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[5]  Sangbae Kim,et al.  High-speed bounding with the MIT Cheetah 2: Control design and experiments , 2017, Int. J. Robotics Res..

[6]  Kevin Blankespoor,et al.  BigDog, the Rough-Terrain Quadruped Robot , 2008 .

[7]  Simone C Niquille Regarding the Pain of SpotMini: Or What a Robot's Struggle to Learn Reveals about the Built Environment , 2019 .

[8]  Wei Shen,et al.  Indirect adaptive robust dynamic surface control in separate meter-in and separate meter-out control system , 2017 .

[9]  Chee-Meng Chew,et al.  Virtual Model Control: An Intuitive Approach for Bipedal Locomotion , 2001, Int. J. Robotics Res..

[10]  Junzheng Wang,et al.  Compliance control for a hydraulic bouncing system. , 2018, ISA transactions.

[11]  Wang Junzheng,et al.  Design and simulation of a hydraulic biped robot , 2013, Proceedings of the 32nd Chinese Control Conference.

[12]  Junjie Yang,et al.  SLIP Model-Based Foot-to-Ground Contact Sensation via Kalman Filter for Miniaturized Quadruped Robots , 2019, ICIRA.

[13]  Junzheng Wang,et al.  Fractional Order Impedance Control , 2020, IEEE Access.

[14]  Wang,et al.  Application of a new adaptive robust controller design method to electro-hydraulic servo system , 2016 .

[15]  Marc H. Raibert,et al.  Legged Robots That Balance , 1986, IEEE Expert.

[16]  Junzheng Wang,et al.  Gait Planning and Compliance Control of a Biped Robot on Stairs with Desired ZMP , 2014 .