Generation of Joint Trajectories Using Hybrid Automate-Based Model: A Rocking Block-Based Approach

Human walk is the combination of seven different discrete subphases. It is difficult to express the one gait cycle as a whole. To develop the human like bipedal robot, the walk cycle is divided into seven discrete subphases. Each subphases has its own continuous dynamics. To express this discrete behavior for the development of the more accurate bipedal robot, the hybrid automata are proposed. The bipedal walk is configured as the rocking block model. It is the first attempt to express the bipedal walk as a rocking block. During double support phases, it is configured as a vertical rectangular plane, and during the left and right leg swing, it is configured as the tilt of the rectangular rocking block in the left and right direction. In this paper, we have configured the bipedal robot as the rocking block before and after impact. The novelty of work is the configuration of bipedal walk as the rocking block and the development of hybrid automata. We configured the hybrid automata dynamic walk model for individual subjects. The trajectory generated by the model is compared with the two models of OpenSim bipedal Gait2354 and normal walk. This paper presents a new modeling technique of bipedal locomotion using hybrid automata. The hip, knee, and ankle trajectories have been synthesized from the model. The stability margin has been defined analytically. Similarly, these trajectories have been fed to a real humanoid robot HOAP2, which were able to perform the stable walking with these trajectories.

[1]  Auke Jan Ijspeert,et al.  Biologically inspired CPG based above knee active prosthesis , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Jun Morimoto,et al.  Learning from demonstration and adaptation of biped locomotion , 2004, Robotics Auton. Syst..

[3]  Gora Chand Nandi,et al.  Toward Developing a Computational Model for Bipedal Push Recovery–A Brief , 2015, IEEE Sensors Journal.

[4]  Jie Zhao,et al.  Bifurcations and chaos in passive dynamic walking: A review , 2014, Robotics Auton. Syst..

[5]  Thomas A. Henzinger,et al.  Hybrid Automata with Finite Bisimulatioins , 1995, ICALP.

[6]  O. Stursberg,et al.  Continuous-discrete interactions in chemical processing plants , 2000, Proceedings of the IEEE.

[7]  Gora Chand Nandi,et al.  Study of humanoid Push recovery based on experiments , 2013, 2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE).

[8]  Pravin Varaiya,et al.  What's decidable about hybrid automata? , 1995, STOC '95.

[9]  Gora Chand Nandi,et al.  Biometric gait identification based on a multilayer perceptron , 2015, Robotics Auton. Syst..

[10]  Gora Chand Nandi,et al.  Biologically-inspired push recovery capable bipedal locomotion modeling through hybrid automata , 2015, Robotics Auton. Syst..

[11]  G. C. Nandi,et al.  Biped model based on human Gait pattern parameters for sagittal plane movement , 2013, 2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE).

[12]  Thomas A. Henzinger,et al.  The theory of hybrid automata , 1996, Proceedings 11th Annual IEEE Symposium on Logic in Computer Science.

[13]  Gora Chand Nandi,et al.  Less computationally intensive fuzzy logic (type-1)-based controller for humanoid push recovery , 2015, Robotics Auton. Syst..

[14]  Thomas A. Henzinger,et al.  The Algorithmic Analysis of Hybrid Systems , 1995, Theor. Comput. Sci..

[15]  L Saab,et al.  Generation of human-like motion on anthropomorphic systems using inverse dynamics , 2012, Computer methods in biomechanics and biomedical engineering.

[16]  Bengt Lennartson,et al.  Hybrid systems in process control , 1996 .

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

[18]  Paulo B. Lourenço,et al.  On the dynamics of rocking motion of single rigid‐block structures , 2007 .

[19]  Karl Henrik Johansson,et al.  Dynamical properties of hybrid automata , 2003, IEEE Trans. Autom. Control..

[20]  David E. Orin,et al.  Centroidal dynamics of a humanoid robot , 2013, Auton. Robots.

[21]  Gora Chand Nandi,et al.  Robust and accurate feature selection for humanoid push recovery and classification: deep learning approach , 2017, Neural Computing and Applications.

[22]  S. Shankar Sastry,et al.  Conflict resolution for air traffic management: a study in multiagent hybrid systems , 1998, IEEE Trans. Autom. Control..

[23]  Ales Ude,et al.  Planning of joint trajectories for humanoid robots using B-spline wavelets , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[24]  R. Horowitz,et al.  Control design of an automated highway system , 2000, Proceedings of the IEEE.

[25]  Atsushi Nakazawa,et al.  Learning from Observation Paradigm: Leg Task Models for Enabling a Biped Humanoid Robot to Imitate Human Dances , 2007, Int. J. Robotics Res..

[26]  S. Hogan On the dynamics of rigid-block motion under harmonic forcing , 1989, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[27]  C. Pinello,et al.  Automotive engine control and hybrid systems: challenges and opportunities , 2000, Proceedings of the IEEE.

[28]  In-Young Yang,et al.  Characterization on the rocking vibration of rigid blocks under horizontal harmonic excitations , 2012 .

[29]  Cheong Boon Soh,et al.  Assessment of Foot Trajectory for Human Gait Phase Detection Using Wireless Ultrasonic Sensor Network , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[30]  Romain Meeusen,et al.  Human–Robot Interaction: Kinematics and Muscle Activity Inside a Powered Compliant Knee Exoskeleton , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.