未來發展

1. 即時影像傳輸：

目前將防震後的影像資訊直接透過無線網路 802.11 傳輸，由於影像資料量 大經過網路的傳輸會降低其畫面更新率，使得在遠端監控畫面接收影像之防震 效果較不明顯，未來可在影像處理演算法裡加入影像壓縮的功能，將資料壓縮 後即使透過網路傳輸也不降低其畫面順暢度，監控端可獲得一平穩之視訊。

2. 分散視覺系統目標位置估測方面：

由於分散視覺間影像資訊的傳輸是透過無線網路，資料傳輸會有 delay 的 問題，對於動態目標位置的估算較不精確，未來可利用 Kalman 估測器加上預 測目標位置的功能，使得對於動態目標也可即時估測其位置。另外由於目前只 針對影像中特定顏色為特徵來達成目標物辨識，未來可多利用影像中的各種資 訊：線條、形狀等等特徵，使得分散視覺系統可針對各種形態的目標物達成位 置的估測，並可建構出目標物在空間中的輪廓，建立更多的資訊使得在搬運目 標任務上能更成功地執行。

3. 加強合作策略：

目前透過影像回授資訊作為合作搬運目標時狀態判斷的依據，但由於攝影 機視角有限的關係無法確認搬運是否成功，未來可增加壓力感測器在搬運的機 構上，並以此資訊加入合作策略，由於壓力感測器可提供是否碰觸到目標物的

感測資訊，以此設計機制判斷搬運是否成功，否則持續執行搬運動作，未來可 以更多的感測資訊加強合作策略使機器人在各種情況下皆可成功地搬運目標。

參考文獻

[1] D. Calisi, D. Nardi, K. Ohno, and S. Tadokoro. “A Semi-autonomous Tracked Robot System for Rescue Missions,” SICE Annual Conference, pp.2066-2069, Aug. 2008.

[2] T. Kamegawa, T. Yamasaki, and F. Matsuno, “Evaluation of Snake-like Rescue Robot Kohga for Usability of Remote Control,” IEEE International Workshop on Safety, Security and Rescue Robotics, pp. 25-30, 2005.

[3] RoBoCup. http://www.robocup.org.

[4] Y. M. Yeh, S. J. Wang , and H. C. Chiang,“Digital Camcorder Image Stabilizer Based on Gray-coded Bit-plane Block Matching,” Optical Engineering, vol. 40, pp. 112-120, Oct. 2001.

[5] S. Erturk, “Digital Image Stabilization with Sub-image Phase Correlation Based Global Motion Estimation,” IEEE Trans. on Consumer Electronics, vol.

49, no. 4, pp. 1320-1325, Nov. 2003.

[6] J. Y. Chang, W. F. Hu, M. H. Cheng, and B. S. Chang,“Digital Image Translational and Rotational Motion Stabilization Using Optical Flow Technique,” IEEE Trans. on Consumer Electronics, vol. 48, no. 1, pp. 108-115, Nov. 2002.

[7] H. C. Chang, S. H. Lai, and K. R. Lu, “A Robust Real-time Video Stabilization Algorithm,” Journal of Visual Communication and Image Representation, vol.

17, no. 3, pp. 659-673, Jun. 2006.

[8] J. S. Jin, Z. Zhu, and G. Xu, “A Stable Vision System for Moving Vehicles,”

IEEE Trans. on Intelligent Transportation Systems, vol. 1, no. 1, pp. 32-39, March 2000.

[9] S. C. Hsu, S. F. Liang, and C. T. Lin, “A Robust Digital Image Stabilization

Technique Based on Inverse Triangle Method and Background Detection,＂

IEEE Trans. on Consumer Electronics, vol. 51, no. 2, pp. 335-343, May 2005.

[10] J. H. Lee, K. W. Lim, B. C. Song, and J. B. Ra , “A Fast Multi-Resolution Block Matching Algorithm and its LSI Architecture for Low Bit-Rate Video Coding,” IEEE Trans. on Circuit and Systems for Video Technology, vol. 11, no.

12, Dec. 2001.

[11] A. Barton-Sweeney, D. Lymberopoulos, and A.Sawides, “Sensor Localization and Camera Calibration in Distributed Camera Sensor Networks,” 3rd International Conference on Broadband Communications, Networks and Systems, pp. 1-10, Oct. 2006.

[12] D. Devarajan and R. J. Radke, “Distributed Metric Calibration of Large Camera Networks,” 1st Workshop on Broadband Advanced Sensor Networks, 2004.

[13] W. E. Mantzel, C. Hyeokho, and R.G. Baraniuk , “Distributed Camera Network Localization,” Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, vol. 2, pp. 1381-1386, Nov. 2004.

[14] K. Qian, X. Ma, X. Dai, and C. Hu, “A Multi-camera Approach to Tracking and Localization of People with Coexisting Robots,” Intelligent Control and Automation, 2008, pp. 5162-5167, June 2008

[15] P. Aarabi, “The Application of Spatial Likelihood Functions to Multi-camera Object Localization,” Proc. of SPIE, vol. 4385, 2001.

[16] J. Bouguet, Instrinsic Camera Calibration: a Software Toolbox for Matlab.

http://www.vision.caltech.edu/bouguetj/calib doc/.

[17] Y. Wang, H. Lang, and C. W. Silva, “Visual Servo Control and Parameter Calibration for Mobile Multi-robot Cooperative Assembly Tasks,” IEEE International Conference on Automation and Logistics, pp. 635-639, Sept. 2008.

[18] G. Chesi, G. L. Mariottini, D. Prattichizzo, and A. Vicino, “Epipole-based Visual

Servoing for Mobile Robots,” Advanced Robotics, vol. 20, no. 2, pp. 255–280, 2006.

[19] S. Kim and S. Y. Oh, “Hybrid Position and Image Based Visual Servoing for Mobile Robots,” Journal of Intelligent and Fuzzy Systems, vol. 18, no. 1, pp. 73-28, 2007.

[20] O. Simonin and O. Grunder, “A Cooperative Multi-robot Architecture for Moving a Paralyzed Robot,” Mechatronics, vol. 19, no. 4, pp. 463-470, June 2009.

[21] C. Zieliński and P. Trojanek, “Stigmergic Cooperation of Autonomous Robots,”

Mechanism and Machine Theory, vol. 44, no. 4, pp. 656-670, April 2009.

[22] A. Cherubini, F. Chaumette, and G. Oriolo, “An Image-based Visual Servoing Scheme for Following Paths with Nonholonomic Mobile Robots,” International Conference on Control, Automation, Robotics and Vision, pp. 108-113, Dec.

2008.

[23] K. Seo and J. S. Lee, “Kinematic Path-following Control of a Mobile Robot under Bounded Angular Velocity Error,” Advanced Robotics, vol. 20, no. 1, pp.

1–23, 2006.

[24] M. Ghaffari, S. Ali, V. Murthy, X. Liao, and J. Gaylor, “Design of an Unmanned Ground Vehicle, Bearcat III, Theory and Practice,” Journal of Robotic Systems, vol. 21, no. 9, pp. 471-480 July 2004.

[25] G. Welch and G. Bishop, An Introduction to the Kalman Filter, Department of Computer Science University of North Carolina at Chapel Hill, NC 27599-3175, 1995.

[26] R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice-Hall, 2002.

[27] MATLAB^® (2004). Image Processing Toolbox User's Guide Version 5,