Abstract
This paper presents a vision-tracking system for mobile robots, which travel in a 3-dimentional environment. The developed system controls pan and tilt actuators attached to a camera so that a target is always directly in the line of sight of the camera. This is achieved by using data from robot wheel encoders, a 3-axis accelerometer, a 3-axis gyroscope, pan and tilt motor encoders, and camera. The developed system is a multi-rate sampled data system, where the sampling rate of the camera is different with that of the other sensors. For the accurate estimation of the robot velocity, the developed system detects the slip of robot wheels, by comparing the data from the encoders and the accelerometer. The developed system estimates the target position by using an extended Kalman filter. The experiments are performed to show the tracking performance of the developed system in several motion scenarios, including climbing slopes and slip cases.
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References
Espiau, B., Chaumette, F., Rives, P.: A New Approach to Visual Servoing in Robotics. IEEE Transactions on Robotics and Automation 8(3), 313–326 (1992)
Hutchinson, S., Hager, G.D., Corke, P.I.: A tutorial on visual servo control. IEEE Transactions on Robotics and Automation 12(5), 615–670 (1996)
Corke, P.I., Hutchinson, S.: A New Partitioned Approach to Image Based Visual Servo Control. IEEE Transactions on Robotics and Automation 17(4), 507–515 (2001)
Hamel, T., Mahony, R.: Visual Servoing of an Under-Actuated Dynamic Rigid-Body System: An Image-Based Approach. IEEE Transactions on Robotics and Automation 18(2), 507–515 (2002)
Chena, J., Dawsonb, D.M., Dixonc, W.E., Chitrakaran, V.K.: Navigation Function-Based Visual Servo Control. Automatica 43(7), 1165–1177 (2007)
Algrain, M.C., Quinn, J.: Accelerometer Based Line-of-Sight Stabilization Approach for Pointing and Tracking Systems. In: Second IEEE Conference on Control Applications, vol. 1, pp. 159–163 (1993)
Panerai, F., Metta, G., Sandini, G.: Visuo-Inertial Stabilization in Space-Variant Binocular Systems. Robotics and Autonomous Systems 30(1-2), 195–214 (2000)
Xie, S., Luo, J., Gong, Z., Ding, W., Zou, H., Fu, X.: Biomimetic Control of Pan-Tilt-Zoom Camera for Visual Tracking Based-on an Autonomous Helicopter. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2138–2143 (2007)
Lenz, A., Balakrishnan, T., Pipe, A.G., Melhuish, C.: An Adaptive Gaze Stabilization Controller Inspired by the Vestibulo-Ocular Reflex. Bioinspiration & Biomimetics 3, 1–11 (2008)
Hwangbo, M., Kim, J., Kanade, T.: Inertial-Aided KLT Feature Tracking for a Moving Camera. In: Intelligent Robots and Systems, pp. 1909–1916 (2009)
Hwang, W., Park, J., Kwon, H., Anjum, M., Kim, J., Lee, C., Kim, K., Cho, D.D.: Vision Tracking System for Mobile Robots Using Two Kalman Filters and a Slip Detector. In: International Conference on Control, Automation and Systems, pp. 2041–2046 (2010)
Park, J., Hwang, W., Kwon, H., Kim, K., Cho, D.D.: A Novel Line of Sight Control System for a Robot Vision Tracking System, Using Vision Feedback and Motion-Disturbance Feedforward Compensation. Robotica (accepted)
Kim, T., Bahn, W., Lee, C., Lee, T., Shaikh, M.M., Kim, K.: Vision System for Mobile Robots for Tracking Moving Targets, Based on Robot Motion and Stereo Vision Information. In: 2011 IEEE/SICE International Symposium on System Integration, pp. 634–639 (2011)
Jun, B., Kim, D.: Robust Real-Time Face Detection Using Face Certainty Map. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 29–38. Springer, Heidelberg (2007)
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Kim, TI. et al. (2012). A Robotic Pan and Tilt 3-D Target Tracking System by Data Fusion of Vision, Encoder, Accelerometer, and Gyroscope Measurements. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33515-0_66
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DOI: https://doi.org/10.1007/978-3-642-33515-0_66
Publisher Name: Springer, Berlin, Heidelberg
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