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Inertial and Vision Sensor Based End-Effector Sensing and Control for Robot Manipulators

[+] Author Affiliations
H. Cheng, M. Tomizuka

University of California at Berkeley, Berkeley, CA

Paper No. DSCC2010-4286, pp. 563-568; 6 pages
  • ASME 2010 Dynamic Systems and Control Conference
  • ASME 2010 Dynamic Systems and Control Conference, Volume 2
  • Cambridge, Massachusetts, USA, September 12–15, 2010
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4418-2 | eISBN: 978-0-7918-3884-6
  • Copyright © 2010 by ASME


In the application of industrial robot manipulators, it is often desirable to obtain accurate position and velocity information regarding the end-effector. Estimations based on motor-side encoders alone are often inaccurate due to joint flexibilities and errors in the robot link kinematics. A vision based approach may also be insufficient due to its low sampling rate and image processing and transportation delay. However, with additional accelerometer measurements, a kinematic Kalman filter (KKF) can be formulated to estimate the end-effector motion accurately without encoder signals. The estimation results can be utilized for real time tracking control effectively. In this paper a multirate kinematic Kalman filter (KKF) scheme is formulated using vision and acceleration measurements from the end-effector. Estimations based on the scheme are utilized as feedback signals for tracking control. The effectiveness of the proposed approach is demonstrated by experiments on a single joint direct drive setup.

Copyright © 2010 by ASME



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