Terminal sliding mode control of a virtual humanoid robot

This manuscript deals with the problem of controlling a virtualized humanoid robot with 16 degrees of freedom (DOF), each corresponding to the articulation in a real human being. That is, three DOF for each leg in the sagittal plane and one for the abduction movement; three DOF for each arm in the sagittal plane and one for the waist. The tracking trajectory problem of any humanoid robot like the classical biped robots requires a control algorithm with robustness against parametric uncertainties, fast response and even with finite-time convergence. These main characteristics are easily covered by sliding mode controllers. This manuscript implements a terminal second order sliding mode (TSOSM) controller to ensure the finite-time tracking trajectory of each articulation of the humanoid robot to the ones that define a classical walking pattern obtained by bio-mechanical studies. The TSOSM is implemented in a virtual platform developed in a computer-aided design software.

[1]  C. Hargraves,et al.  DIRECT TRAJECTORY OPTIMIZATION USING NONLINEAR PROGRAMMING AND COLLOCATION , 1987 .

[2]  Christine Chevallereau,et al.  Models, feedback control, and open problems of 3D bipedal robotic walking , 2014, Autom..

[3]  Isaac Chairez,et al.  Integrated wearable and self-carrying active upper limb orthosis , 2018, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[4]  Leonid M. Fridman,et al.  Continuous terminal sliding-mode controller , 2016, Autom..

[5]  A. Levant.  Robust exact differentiation via sliding mode technique , 1998 .

[6]  Naoyuki Kubota,et al.  Biologically Inspired Control System for 3-D Locomotion of a Humanoid Biped Robot , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[7]  Misael Sanchez-Magos,et al.  Adaptive Proportional Derivative Controller of Cooperative Manipulators , 2018 .

[8]  Bernd Henze,et al.  Good Posture, Good Balance: Comparison of Bioinspired and Model-Based Approaches for Posture Control of Humanoid Robots , 2016, IEEE Robotics & Automation Magazine.

[9]  Aaron D. Ames,et al.  A Human-Inspired Hybrid Control Approach to Bipedal Robotic Walking , 2011 .

[10]  Kazuhito Yokoi,et al.  Real-Time Planning of Humanoid Robot's Gait for Force-Controlled Manipulation , 2007 .

[11]  Isaac Chairez,et al.  A New Homogeneous Quasi-Continuous Second Order Sliding Mode Control , 2014 .

[12]  Qiang Huang,et al.  Bioinspired Control of Walking With Toe-Off, Heel-Strike, and Disturbance Rejection for a Biped Robot , 2017, IEEE Transactions on Industrial Electronics.

[13]  Bernard Brogliato,et al.  Modeling, stability and control of biped robots - a general framework , 2004, Autom..

[14]  Nikolaos G. Tsagarakis,et al.  Model-Free Robust Adaptive Control of Humanoid Robots With Flexible Joints , 2017, IEEE Transactions on Industrial Electronics.

[15]  Marc D. Killpack,et al.  A New Soft Robot Control Method: Using Model Predictive Control for a Pneumatically Actuated Humanoid , 2016, IEEE Robotics & Automation Magazine.

[16]  Changyin Sun,et al.  Adaptive Neural Network Control of Biped Robots , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[17]  Isaac Chairez,et al.  Output feedback control of a skid-steered mobile robot based on the super-twisting algorithm , 2017 .

[18]  Don Joven Agravante,et al.  Visual Servoing in an Optimization Framework for the Whole-Body Control of Humanoid Robots , 2017, IEEE Robotics and Automation Letters.

[19]  Yannick Aoustin,et al.  Finite time tracking of a fully actuated biped robot with pre-specified settling time: A second order sliding mode synthesis , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).