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Design and application of the stereo vision manipulator with novel scheduling policies control

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Abstract

This main purpose of this paper is to promote the efficiency of a control system using a scheduling policies control design. In this system, the management of a computer’s input and output information is handled appropriately by the program language. The scheduling policies control design is used in the robotic arm’s tracking system. The advantage of this control design is to activate each procedure running simultaneously when the transient overload of the information’s input and output in the control system occurs. Therefore, the time run in the scheduling policies control system will be shorter than that of a traditional control system in which each procedure is lined up for running. In this paper, case studies of the scheduling police control application used in image tracking vision control are introduced. The results reveal that the speed of the tracking system can be improved by using the scheduling police technique under an immediate procedure plan.

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References

  1. Barnard ST, Thompson WB (1980) Disparity analysis of images. IEEE Trans Pattern Anal Mach Intell 2(4):330–340. doi:10.1109/TPAMI.1980.4767032

    Google Scholar 

  2. Bertozzi M, Broggi A (1998) GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection. IEEE Trans Image Process 7(1):62–81. doi:10.1109/83.650851

    Article  Google Scholar 

  3. Han S-H, Seo WH, Yoon KS, Lee M-H (1999) Real-time control of an industrial robot using image-based visual servoing. Proceedings of the 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1762–1796. doi:10.1109/IROS.1999.811733

  4. Hu B, Michel AN (1999) Some qualitative properties of multirate digital control systems. IEEE Trans Autom Control 44(4):765–770. doi:10.1109/CDC.1997.649518

    Article  MathSciNet  MATH  Google Scholar 

  5. John M, Ovidiu G, Paul F, Whelan (2003) Robust 3-D landmark tracking using trinocular vision. Vision System Laboratory. School of Electronic Engineering Dublin City University, pp. 221–229. doi:10.1117/12.463730

  6. Kidono K, Miura J, Shirai Y (2002) Autonomous visual navigation of a mobile robot using a human-guided experience. Proc Elsevier Int Conf Robot Auton Syst 40(2):121–130. doi:10.1016/S0921-8890(02)00237-3

    Article  Google Scholar 

  7. Kuo HC, Wu LJ (2002) An image tracking system for welded seams using fuzzy logic. J Mater Process Technol 120(1–3):169–185. doi:10.1016/S0924-0136(01)01155-4

    Article  Google Scholar 

  8. Lobo J, Queiroz C, Dias J (2003) World feature detection and mapping using stereovision and inertial sensors. Proc Elsevier Int Conf Robot Auton Syst 44(1):69–81. doi:10.1016/S0921-8890(03)00011-3

    Article  Google Scholar 

  9. Mohan R, Nevatia R (1989) Using perceptual organization to extract 3D structures. IEEE Trans Pattern Anal Mach Intell 11(11):1121–1139. doi:10.1109/34.42852

    Article  Google Scholar 

  10. Murray D, Jennings C (1997) Stereo vision based mapping and navigation for mobile robots. Robot Autom IEEE Int Conf 2:1694–1699. doi:10.1109/ROBOT.1997.614387

    Article  Google Scholar 

  11. Ohya I, Kosaka A, Kak A (1998) Vision-based navigation by a mobile robot with obstacle avoidance using single-camera vision and ultrasonic sensing. Vision Res 14(6):969–978. doi:10.1109/70.736780

    Google Scholar 

  12. Olson CF, Huttenlocher DP (1997) Automatic target recognition by matching oriented edge pixels. IEEE Trans Image Process 6(1):103–113. doi:10.1109/83.552100

    Article  Google Scholar 

  13. Palopoli L, Abeni L, Bolognini G, Allotta B, Conticelli F (2002) Novel scheduling policies in real-time multithread control system design. Pregamon Control Eng Pract 10:1091–1110. doi:10.1016/S0967-0661(02)00054-0

    Article  Google Scholar 

  14. Seara JF, Schmidt G (2004) Intelligent gaze control for vision-guided humanoid walking: methodological aspects. Robot Auton Syst 48:231–248. doi:10.1016/j.robot.2004.07.003

    Article  Google Scholar 

  15. Starck JL, Murtagh F, Candes EJ, David DL (2003) Gray and color image contrast enhancement by the curvelet transform. IEEE Trans Image Process 12(6):706–717. doi:10.1109/TIP.2003.813140

    Article  MathSciNet  Google Scholar 

  16. Winters N, Santos-Victor J (2002) Information sampling for vision-based robot navigation. Robot Auton Syst 41:145–159. doi:10.1016/S0921-8890(02)00278-6

    Article  Google Scholar 

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Correspondence to Kuei-Shu Hsu.

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Hsu, KS., Peng, L. & Yu, C. Design and application of the stereo vision manipulator with novel scheduling policies control. Multimed Tools Appl 67, 249–268 (2013). https://doi.org/10.1007/s11042-011-0867-1

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