Impact Mitigation for Dynamic Legged Robots with Steel Wire Transmission Using Nonlinear Active Compliance Control

Impact mitigation is crucial to the stable locomotion of legged robots, especially in high-speed dynamic locomotion. This paper presents a leg locomotion system, including the nonlinear active compliance control and the active impedance control for the steel wire transmission-based legged robot. The developed control system enables high-speed dynamic locomotion with excellent impact mitigation and leg position tracking performance, where three strategies are applied. a) The feed-forward controller is designed according to the linear motor-leg model with the information of Coulomb friction and viscous friction. b) Steel wire transmission model-based compensation guarantees ideal virtual spring compliance characteristics. c) Nonlinear active compliance control and active impedance control ensure better impact mitigation performance than linear scheme and guarantee position tracking performance. The proposed control system is verified on a real robot named SCIT Dog, and the experiment demonstrates the ideal impact mitigation ability in high-speed dynamic locomotion without any passive spring mechanism.

[1]  Berno J. E. Misgeld,et al.  Experimental Validation of a Torque-Controlled Variable Stiffness Actuator Tuned by Gain Scheduling , 2018, IEEE/ASME Transactions on Mechatronics.

[2]  Bernhard Penzlin,et al.  Low Impedance-Guaranteed Gain-Scheduled GESO for Torque-Controlled VSA With Application of Exoskeleton-Assisted Sit-to-Stand , 2021, IEEE/ASME Transactions on Mechatronics.

[3]  Pablo González de Santos,et al.  Generating continuous free crab gaits for quadruped robots on irregular terrain , 2005, IEEE Transactions on Robotics.

[4]  N. Hogan,et al.  Impedance Control:An Approach to Manipulation,Parts I,II,III , 1985 .

[5]  W. Marsden I and J , 2012 .

[6]  Jae-Bok Song,et al.  Design and Control of a Variable Stiffness Actuator Based on Adjustable Moment Arm , 2012, IEEE Transactions on Robotics.

[7]  Jae-Bok Song,et al.  Acceleration estimator for low-velocity and low-acceleration regions based on encoder position data , 2001 .

[8]  Nikolaos G. Tsagarakis,et al.  A new variable stiffness actuator (CompAct-VSA): Design and modelling , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Rieko Osu,et al.  The central nervous system stabilizes unstable dynamics by learning optimal impedance , 2001, Nature.

[10]  Matthew M. Williamson,et al.  Series elastic actuators , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[11]  Anthony Tzes,et al.  Genetic-based fuzzy clustering for DC-motor friction identification and compensation , 1998, IEEE Trans. Control. Syst. Technol..

[12]  Darwin G. Caldwell,et al.  Towards versatile legged robots through active impedance control , 2015, Int. J. Robotics Res..

[13]  Jonas Buchli,et al.  Is Active Impedance the Key to a Breakthrough for Legged Robots? , 2013, ISRR.

[14]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[15]  M. Alexander,et al.  Principles of Neural Science , 1981 .

[16]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation , 1984, 1984 American Control Conference.

[17]  Albert Wang,et al.  Proprioceptive Actuator Design in the MIT Cheetah: Impact Mitigation and High-Bandwidth Physical Interaction for Dynamic Legged Robots , 2017, IEEE Transactions on Robotics.

[18]  Darwin G. Caldwell,et al.  Model-Based Hydraulic Impedance Control for Dynamic Robots , 2015, IEEE Transactions on Robotics.

[19]  Andrew A Biewener,et al.  Scaling of the spring in the leg during bouncing gaits of mammals. , 2014, Integrative and comparative biology.

[20]  N. Hogan Adaptive control of mechanical impedance by coactivation of antagonist muscles , 1984 .

[21]  Hartmut Geyer,et al.  A Muscle-Reflex Model That Encodes Principles of Legged Mechanics Produces Human Walking Dynamics and Muscle Activities , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[22]  Dong Jin Hyun,et al.  High speed trot-running: Implementation of a hierarchical controller using proprioceptive impedance control on the MIT Cheetah , 2014, Int. J. Robotics Res..

[23]  R. Siegwart,et al.  Efficient and Versatile Locomotion With Highly Compliant Legs , 2013, IEEE/ASME Transactions on Mechatronics.

[24]  Albert Wang,et al.  Actuator design for high force proprioceptive control in fast legged locomotion , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[25]  W. Hager,et al.  and s , 2019, Shallow Water Hydraulics.

[26]  Jianrong Tan,et al.  A Novel Design of Serial Variable Stiffness Actuator Based on an Archimedean Spiral Relocation Mechanism , 2018, IEEE/ASME Transactions on Mechatronics.

[27]  Nikolaos G. Tsagarakis,et al.  Development and control of a series elastic actuator equipped with a semi active friction damper for human friendly robots , 2014, Robotics Auton. Syst..

[28]  Auke Jan Ijspeert,et al.  Central pattern generators for locomotion control in animals and robots: A review , 2008, Neural Networks.

[29]  Jonas Buchli,et al.  Is Active Impedance the Key to a Breakthrough for Legged Robots , 2016 .