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Visual Servoing for Robot Manipulators Considering Sensing and Dynamics Limitations

[+] Author Affiliations
Cong Wang, Chung-Yen Lin, Masayoshi Tomizuka

University of California, Berkeley, CA

Paper No. DSCC2013-3833, pp. V003T40A003; 8 pages
  • ASME 2013 Dynamic Systems and Control Conference
  • Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control
  • Palo Alto, California, USA, October 21–23, 2013
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5614-7
  • Copyright © 2013 by ASME


This paper presents a control scheme of visual servoing. Real-time vision guidance is necessary in many desirable applications of industrial manipulators. Challenge comes from the limitations of visual sensing and robot dynamics. Typical industrial machine vision systems have low sampling rate and large latency. In addition, due to the large inertia of industrial manipulators, a proper consideration of robot dynamics is important. In particular, actuator saturation may cause undesirable response. In this paper, an adaptive tracking filter is used for sensing compensation. Based on the compensated vision feedback, a two-layer controller is formulated using multi-surface sliding control. System kinematics and dynamics are decoupled and handled by the two layers of the controller respectively. Further, a constrained optimal control approach is adopted to avoid actuator saturation. Validation is conducted using a SCARA robot.

Copyright © 2013 by ASME



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