Vision-based model predictive control for within-hand precision manipulation with underactuated grippers

Precision manipulation with underactuated hands is a challenging problem due to difficulties in obtaining precise gripper, object and contact models. Using vision feedback provides a degree of robustness to modeling inaccuracies, but conventional visual servoing schemes may suffer from performance degradation if inaccuracies are large and/or unmodeled phenomena (e.g. friction) have significant effect on the system. In this paper, we propose the use of Model Predictive Control (MPC) framework within a visual servoing scheme to achieve high performance precision manipulation even with very rough models of the manipulation process. With experiments using step and periodic reference signals (in total 204 experiments), we show that the utilization of MPC provides superior performance in terms of accuracy and efficiency comparing to the conventional visual servoing methods.

[1]  Luc Soler,et al.  Active filtering of physiological motion in robotized surgery using predictive control , 2005, IEEE Transactions on Robotics.

[2]  J. Gamez Garcia,et al.  Model predictive position/force control of an anthropomorphic robotic arm , 2015, 2015 IEEE International Conference on Industrial Technology (ICIT).

[3]  Luc Soler,et al.  Beating heart tracking in robotic surgery using 500 Hz visual servoing, model predictive control and an adaptive observer , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[4]  Olac Fuentes,et al.  Experimental evaluation of uncalibrated visual servoing for precision manipulation , 1997, Proceedings of International Conference on Robotics and Automation.

[5]  L. A. Muñoz.  Robust dexterous manipulation: a methodology using visual servoing , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[6]  Aaron M. Dollar,et al.  Vision-based precision manipulation with underactuated hands: Simple and effective solutions for dexterity , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[7]  Chun-Yi Su,et al.  Vision-Based Model Predictive Control for Steering of a Nonholonomic Mobile Robot , 2016, IEEE Transactions on Control Systems Technology.

[8]  Walter Lucia,et al.  A model predictive control scheme for mobile robotic vehicles in dynamic environments , 2013, 52nd IEEE Conference on Decision and Control.

[9]  Antonio Bicchi,et al.  On the mobility and manipulability of general multiple limb robots , 1995, IEEE Trans. Robotics Autom..

[10]  Suguru Arimoto,et al.  Grasping and position control for multi-fingered robot hands with uncertain Jacobian matrices , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[11]  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.

[12]  Aaron M. Dollar,et al.  Open-Loop Precision Grasping With Underactuated Hands Inspired by a Human Manipulation Strategy , 2013, IEEE Transactions on Automation Science and Engineering.

[13]  Allison M. Okamura,et al.  An overview of dexterous manipulation , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[14]  François Chaumette,et al.  Visual servo control. I. Basic approaches , 2006, IEEE Robotics & Automation Magazine.

[15]  Aaron D. Ames,et al.  Model predictive control of underactuated bipedal robotic walking , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[16]  Olac Fuentes,et al.  Acquiring Visual-Motor Models for Precision Manipulation with Robot Hands , 1996, ECCV.

[17]  Dimos V. Dimarogonas,et al.  A self-triggered visual servoing model predictive control scheme for under-actuated underwater robotic vehicles , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[18]  Angela P. Schoellig,et al.  Learning-based nonlinear model predictive control to improve vision-based mobile robot path-tracking in challenging outdoor environments , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[19]  Chien Chern Cheah,et al.  Neural Network Control of Multifingered Robot Hands Using Visual Feedback , 2009, IEEE Transactions on Neural Networks.