Dual Control for Jerk-Driven Robotics in Rehabilitative Planar Applications

This study compares a set of strategies to plan and control the trajectory of a robotic device in a planar workspace. These strategies are based on an affective application of jerk-laws able to indicate undesirable conditions (e.g., vibrations) facilitating the device control. The jerk is the time derivative of acceleration, and this solution provides an indirect means to control the variation rate of the actuator torques, while avoiding the complex robot dynamic models and their algorithms for computing the dynamics. In order to obtain a smooth trajectory, a regulator to control a robotic device has been developed and validated. It consists of the implementation of two control modules able to (i) generate the predefined trajectory and (ii) guarantee the path tracking, reducing unwanted effects. In this case a simple S-shaped path has been originated by the “trajectory generator module” as a reference movement to rehabilitate upper limb functionality. The numerical simulation and the results of preliminary tests show the efficacy of the proposed approach through the vibration smoothness appraisal associated with the motion profile.

[1]  J. Edward Colgate,et al.  Cobot control , 1997, Proceedings of International Conference on Robotics and Automation.

[2]  Pierre-Jean Barre,et al.  VIBRATION REDUCTION ABILITIES OF SOME JERK-CONTROLLED MOVEMENT LAWS FOR INDUSTRIAL MACHINES , 2005 .

[3]  Alberto Borboni,et al.  Jerk Trajectory Planning for Assistive and Rehabilitative Mechatronic Devices , 2016 .

[4]  W. Rymer,et al.  Robotic Devices for Movement Therapy After Stroke: Current Status and Challenges to Clinical Acceptance , 2002, Topics in stroke rehabilitation.

[5]  Pierre-Jean Barre,et al.  Influence of a Jerk Controlled Movement Law on the Vibratory Behaviour of High-Dynamics Systems , 2005, J. Intell. Robotic Syst..

[6]  Aurelio Piazzi,et al.  Global minimum-jerk trajectory planning of robot manipulators , 2000, IEEE Trans. Ind. Electron..

[7]  Yacine Chitour,et al.  On Human-Robot Co-Manipulation for Handling Tasks: Modeling and Control Strategy , 2012, SyRoCo.

[8]  Zhiwei Luo,et al.  Optimal trajectory formation of constrained human arm reaching movements , 2004, Biological Cybernetics.

[9]  Roger D. Benning,et al.  Active control of mechanical vibrations , 1997, Bell Labs Technical Journal.

[10]  A. Gasparetto,et al.  Model-based trajectory planning for flexible-link mechanisms with bounded jerk , 2013 .

[11]  Vladimir M. Zatsiorsky,et al.  The Mass and Inertia Characteristics of the Main Segments of the Human Body , 1983 .

[12]  A. Gasparetto,et al.  A new method for smooth trajectory planning of robot manipulators , 2007 .

[13]  Akira Abe,et al.  Trajectory planning for residual vibration suppression of a two-link rigid-flexible manipulator considering large deformation , 2009 .

[14]  C. Lin,et al.  Formulation and optimization of cubic polynomial joint trajectories for industrial robots , 1983 .

[15]  K. Tanaka,et al.  Vibration control for cartesian 3 axes robot , 1996, Proceedings of 4th IEEE International Workshop on Advanced Motion Control - AMC '96 - MIE.

[16]  Vahid Azimirad,et al.  Trajectory optimization of flexible link manipulators in point-to-point motion , 2008, Robotica.

[17]  Ali M. S. Zalzala,et al.  A hybrid intelligent active force controller for robot arms using evolutionary neural networks , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[18]  M. M. Hegaze,et al.  A DYNAMIC MODEL OF A SINGLE LINK FLEXIBLE MANIPULATOR , 1997 .

[19]  D. Reinkensmeyer,et al.  Review of control strategies for robotic movement training after neurologic injury , 2009, Journal of NeuroEngineering and Rehabilitation.

[20]  Mark L. Nagurka,et al.  Simulating Discrete and Rhythmic Multi-joint Human Arm Movements by Optimization of Nonlinear Performance Indices , 2006, Biological Cybernetics.

[21]  Hiroyuki Kojima,et al.  Optimal trajectory planning of a two-link flexible robot arm based on genetic algorithm for residual vibration reduction , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[22]  M. Diehl,et al.  Time-energy optimal path tracking for robots: a numerically efficient optimization approach , 2008, 2008 10th IEEE International Workshop on Advanced Motion Control.