机器人视觉伺服研究进展:视觉系统与控制策略

贾丙西; 刘山; 张凯祥; 陈剑

doi:10.16383/j.aas.2015.c140724

机器人视觉伺服研究进展:视觉系统与控制策略

doi: 10.16383/j.aas.2015.c140724

贾丙西^1,2,
刘山^1,2, ,,
张凯祥^1,2,
陈剑^1,2

1.
浙江大学工业控制技术国家重点实验室杭州 310027;
2.
浙江大学控制科学与工程学系杭州 310027

基金项目:

国家自然科学基金(61273133, 61433013)

详细信息

作者简介:
贾丙西浙江大学控制科学与工程学系博士研究生. 主要研究方向为计算机视觉, 视觉伺服控制.E-mail: bxjia@zju.edu.cn

通讯作者:
刘山浙江大学控制科学与工程学系副教授. 2002 年获得浙江大学控制科学与工程学系博士学位. 主要研究方向为学习控制, 视觉伺服控制, 机器人技术.E-mail: sliu@iipc.zju.edu.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2014-10-27
- 修回日期: 2015-01-06
- 刊出日期: 2015-05-20

Survey on Robot Visual Servo Control: Vision System and Control Strategies

JIA Bing-Xi^1,2,
LIU Shan^{1,2
, ,},
ZHANG Kai-Xiang^1,2,
CHEN Jian^1,2

1.
State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027;
2.
Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027

Funds:

Supported by National Natural Science Foundation of China (61273133, 61433013)

摘要

摘要: 视觉伺服控制是机器人系统的重要控制手段. 随着机器人应用需求的日益复杂多样,视觉伺服的研究面临着挑战. 视觉伺服系统的设计主要包括视觉系统、控制策略和实现策略三个方面. 文中对视觉伺服中存在的主要问题进行了分析,重点介绍了视觉系统中改善动态性能和处理噪声的主要技术手段,阐述了处理模型不确定性和约束的控制策略的改进方案,总结了提高视觉伺服系统的可实现性和灵活性的实现策略. 最后,基于当前的研究进展对未来的研究方向进行了展望.
- 视觉伺服 /
- 研究进展 /
- 视觉系统 /
- 控制策略
Abstract: Visual servo control is an important control strategy for robotic systems. With the increasing complication and diversification of robotic applications, the study of visual servo control faces challenges. The design of visual servo systems mainly involves vision systems, control strategies and implementation strategies. In this paper, existing problems in visual servo control are analysed. Approaches in vision systems to improve dynamic performance and to deal with noise are introduced, improvements in control strategies to deal with model uncertainties and constraints are summarized, and implementation strategies to improve the realizability and flexibility of visual servo systems are concluded. Finally, future work is outlined based on the current research progress.
- Visual servo control /
- research development /
- vision system /
- control strategy

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参考文献(133)

[1]	Hutchinson S, Hager G D, Corke P I. A tutorial on visual servo control. IEEE Transactions on Robotics and Automation, 1996, 12(5): 651-670
[2]	[2] Chaumette F, Hutchinson S. Visual servo control I basic approaches. IEEE Robotics Automation Magazine, 2006, 13(4): 82-90
[3]	[3] Chaumette F, Hutchinson S. Visual servo control II advanced approaches. IEEE Robotics Automation Magazine, 2007, 14(1): 109-118
[4]	[4] Staniak M, Zieliński C. Structures of visual servos. Robotics and Autonomous Systems, 2010, 58(8): 940-954
[5]	[5] Azizian M, Khoshnam M, Najmaei N, Patel R. Visual servoing in medical robotics: a survey, Part I: endoscopic and direct vision imaging techniques and applications. The International Journal of Medical Robotics and Computer Assisted Surgery, 2014, 10(3): 263-274
[6]	[6] Azizian M, Najmaei N, Khoshnam M, Patel R. Visual servoing in medical robotics: a survey, Part II: tomographic imaging modalities techniques and applications. The International Journal of Medical Robotics and Computer Assisted Surgery, 2015, 11(1): 67-79
[7]	Lin Jing, Chen Hui-Tang, Wang Yue-Juan, Jiang Ping. Research on robotic visual servoing system. Control Theory Applications, 2000, 17(4): 476-481(林靖, 陈辉堂, 王月娟, 蒋平. 机器人视觉伺服系统的研究. 控制理论与应用, 2000, 17(4): 476-481)
[8]	Zhao Qing-Jie, Lian Guang-Yu, Sun Zeng-Qi. Survey of robot visual servoing. Control and Decision, 2001, 16(6): 849-853(赵清杰, 连广宇, 孙增圻. 机器人视觉伺服综述. 控制与决策, 2001, 16(6): 849-853)
[9]	Xue Ding-Yu, Xiang Long-Jiang, Si Bing-Yu, Xu Xin-He. Classification of robotics visual servoing and its dynamics investigation. Journal of Northeastern University (Natural Science), 2003, 24(6): 543-547(薛定宇, 项龙江, 司秉玉, 徐心和. 视觉伺服分类及其动态过程. 东北大学学报(自然科学版), 2003, 24(6): 543-547)
[10]	Wang Lin-Kun, Xu De, Tan Min. Survey of research on robotic visual servoing. Robot, 2004, 26(3): 277-282(王麟琨, 徐德, 谭民. 机器人视觉伺服研究进展. 机器人, 2004, 26(3): 277-282)
[11]	Fang Yong-Chun. A survey of robot visual servoing. CAAI Transactions on Intelligent Systems, 2008, 3(2): 109-114(方勇纯. 机器人视觉伺服研究综述. 智能系统学报, 2008, 3(2): 109-114)
[12]	Corke P I, Spindler F, Chaumette F. Combining Cartesian and polar coordinates in IBVS. In: Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems. St. Louis, MO: IEEE, 2009. 5962-5967
[13]	Iwatsuki M, Okiyama N. A new formulation of visual servoing based on cylindrical coordinate system. IEEE Transactions on Robotics, 2005, 21(2): 266-273
[14]	Corke P I. Spherical image-based visual servo and structure estimation. In: Proceedings of the 2010 IEEE International Conference on Robotics and Automation. Anchorage, AK: IEEE, 2010. 5550-5555
[15]	Fomena R T, Tahri O, Chaumette F. Distance-based and orientation-based visual servoing from three points. IEEE Transactions on Robotics, 2011, 27(2): 256-267
[16]	Tahri O, Mezouar Y, Chaumette F, Corke P. Decoupled image-based visual servoing for cameras obeying the unified projection model. IEEE Transactions on Robotics, 2010, 26(4): 684-697
[17]	Tahri O, Araujo H, Chaumette F, Mezouar Y. Robust image-based visual servoing using invariant visual information. Robotics and Autonomous Systems, 2013, 61(12): 1588-1600
[18]	Geyer C, Daniilidis K. A unifying theory for central panoramic systems and practical applications. In: Proceedings of the 6th European Conference on Computer Vision. London, UK: Springer-Verlag, 2000. 445-461
[19]	Corke P, Mahony R. Sensing and control on the sphere. In: Proceedings of the 14th International Symposium ISSR. Lucerne, Switzerland: Springer-Verlag Berlin Heidelberg, 2009. 71-85
[20]	Dalal N, Triggs B. Histograms of oriented gradients for human detection. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, CA, USA: IEEE, 2005. 886-893
[21]	Lowe D G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 2004, 60(2): 91-110
[22]	Bay H, Ess A, Tuytelaars T, Van Gool L. Speeded-up robust features (SURF). Computer Vision and Image Understanding, 2008, 110(3): 346-359
[23]	Herisse B, Hamel T, Mahony R, Russotto F X. Landing a VTOL unmanned aerial vehicle on a moving platform using optical flow. IEEE Transactions on Robotics, 2012, 28(1): 77-89
[24]	Malzahn J, Phung A S, Franke R, Hoffmann F, Bertram T. Markerless visual vibration damping of a 3-DOF flexible link robot arm. In: Proceedings of the 41st International Symposium on and 6th German Conference on Robotics. Munich, Germany: VDE, 2010. 1-8
[25]	Tahri O, Chaumette F. Point-based and region-based image moments for visual servoing of planar objects. IEEE Transactions on Robotics, 2005, 21(6): 1116-1127
[26]	Bakthavatchalam M, Chaumette F, Marchand E. Photometric moments: new promising candidates for visual servoing. In: Proceedings of the 2013 IEEE International Conference on Robotics and Automation. Karlsruhe, Germany: IEEE, 2013. 5241-5246
[27]	Bakthavatchalam M, Tahri O, Chaumette F. Improving moments-based visual servoing with tunable visual features. In: Proceedings of the 2014 IEEE International Conference on Robotics and Automation. Hong Kong, China: IEEE, 2014. 6186-6191
[28]	Kallem V, Dewan M, Swensen J P, Hager G D, Cowan N J. Kernel-based visual servoing. In: Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems. San Diego, CA: IEEE, 2007. 1975-1980
[29]	Swensen J P, Kallem V, Cowan N J. Empirical characterization of convergence properties for kernel-based visual servoing. Visual Servoing via Advanced Numerical Methods. London: Springer-Verlag, 2010. 23-38
[30]	Collewet C, Marchand E. Photometric visual servoing. IEEE Transactions on Robotics, 2011, 27(4): 828-834
[31]	Caron G, Marchand E, Mouaddib E M. Photometric visual servoing for omnidirectional cameras. Autonomous Robots, 2013, 35(2-3): 177-193
[32]	Dame A, Marchand E. Mutual information-based visual servoing. IEEE Transactions on Robotics, 2011, 27(5): 958-969
[33]	Dame A, Marchand E. Using mutual information for appearance-based visual path following. Robotics and Autonomous Systems, 2013, 61(3): 259-270
[34]	Malis E, Chaumette F, Boudet S. 2D visual servoing. IEEE Transactions on Robotics and Automation, 1999, 15(2): 238-250
[35]	Lopez-Nicolas G, Gans N R, Bhattacharya S, Sagues C, Guerrero J J, Hutchinson S. Homography-based control scheme for mobile robots with nonholonomic and field-of-view constraints. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2010, 40(4): 1115-1127
[36]	Benhimane S, Malis E. Homography-based 2d visual tracking and servoing. The International Journal of Robotics Research, 2007, 26(7): 661-676
[37]	Lpez-Nicols G, Guerrero J, Sags C. Visual control of vehicles using two-view geometry. Mechatronics, 2010, 20(2): 315-325
[38]	Becerra H M, Lpez-Nicols G, Sags C. A sliding-mode-control law for mobile robots based on epipolar visual servoing from three views. IEEE Transactions on Robotics, 2011, 27(1): 175-183
[39]	Lpez-Nicols G, Guerrero J J, Sags C. Visual control through the trifocal tensor for nonholonomic robots. Robotics and Autonomous Systems, 2010, 58(2): 216-226
[40]	Li Bao-Quan, Fang Yong-Chun, Zhang Xue-Bo. 2D trifocal tensor based visual servo regulation of nonholonomic mobile robots. Acta Automatica Sinica, 2014, 40(12): 2706-2715(李宝全, 方勇纯, 张雪波. 基于2D三焦点张量的移动机器人视觉伺服镇定控制. 自动化学报, 2014, 40(12): 2706-2715)
[41]	Becerra H M, Sags C, Mezouar Y, Hayet J B. Visual navigation of wheeled mobile robots using direct feedback of a geometric constraint. Autonomous Robots, 2014, 37(2): 137-156
[42]	Andreopoulos A, Tsotsos J K. 50 years of object recognition: directions forward. Computer Vision and Image Understanding, 2013, 117(8): 827-891
[43]	Yang H X, Shao L, Zheng F, Wang L, Song Z. Recent advances and trends in visual tracking: a review. Neurocomputing, 2011, 74(18): 3823-3831
[44]	Gil A, Mozos O M, Ballesta M, Reinoso O. A comparative evaluation of interest point detectors and local descriptors for visual SLAM. Machine Vision and Applications, 2010, 21(6): 905-920
[45]	Hartley R, Zisserman A. Multiple View Geometry in Computer Vision. Cambridge: Cambridge University Press, 2003.
[46]	Silveira G, Malis E. Direct visual servoing: vision-based estimation and control using only nonmetric information. IEEE Transactions on Robotics, 2012, 28(4): 974-980
[47]	Silveira G. On intensity-based nonmetric visual servoing. IEEE Transactions on Robotics, 2014, 30(4): 1019-1026
[48]	Ishii I, Tatebe T, Gu Q Y, Moriue Y, Takaki T, Tajima K. 2000 fps real-time vision system with high-frame-rate video recording. In: Proceedings of the 2010 IEEE International Conference on Robotics and Automation. Anchorage. AK: IEEE, 2010. 1536-1541
[49]	Namiki A, Senoo T, Mizusawa S, Ishikawa M. High-speed visual feedback control for grasping and manipulation. Visual Servoing via Advanced Numerical Methods. London: Springer-Verlag, 2010. 39-53
[50]	Wu H Y, Lou L, Chen C C, Hirche S, Khnlenz K. A framework of networked visual servo control system with distributed computation. In: Proceedings of the 2010 11th International Conference on Control Automation Robotics Vision. Singapore: IEEE, 2010. 1466-1471
[51]	Wu H Y, Lou L, Chen C C, Hirche S, Kuhnlenz K. Cloud-based networked visual servo control. IEEE Transactions on Industrial Electronics, 2013, 60(2): 554-566
[52]	Janabi-Sharifi F, Marey M. A Kalman-filter-based method for pose estimation in visual servoing. IEEE Transactions on Robotics, 2010, 26(5): 939-947
[53]	Tsai C Y, Song K T, Dutoit X, Van Brussel H, Nuttin M. Robust visual tracking control system of a mobile robot based on a dual-Jacobian visual interaction model. Robotics and Autonomous Systems, 2009, 57(6-7): 652-664
[54]	Nguyen B M, Ohnishi W, Wang Y, Fujimoto H, Hori Y, Ito K, Odai M, Ogawa H, Takano E, Inoue T, Koyama M. Dual rate Kalman filter considering delayed measurement and its application in visual servo. In: Proceedings of 13th IEEE International Workshop on Advanced Motion Control. Yokohama, Japan: IEEE, 2014. 494-499
[55]	Ibarguren A, Martnez-Otzeta J M, Maurtua I. Particle filtering for industrial 6DOF visual servoing. Journal of Intelligent Robotic Systems, 2014, 74(3-4): 689-696
[56]	Dahmouche R, Andreff N, Mezouar Y, Ait-Aider O, Martinet P. Dynamic visual servoing from sequential regions of interest acquisition. The International Journal of Robotics Research, 2012, 31(4): 520-537
[57]	Comport A I, Marchand E, Chaumette F. Statistically robust 2-D visual servoing. IEEE Transactions on Robotics, 2006, 22(2): 415-420
[58]	Garcia-Aracil N, Malis E, Aracil-Santonja R, Perez-Vidal C. Continuous visual servoing despite the changes of visibility in image features. IEEE Transactions on Robotics, 2005, 21(6): 1214-1220
[59]	Chesi G. Optimal object configurations to minimize the positioning error in visual servoing. IEEE Transactions on Robotics, 2010, 26(3): 584-589
[60]	Iwatani Y. Task selection for control of active-vision systems. IEEE Transactions on Robotics, 2010, 26(4): 720-725
[61]	Spica R, Giordano P R, Chaumette F. Coupling visual servoing with active structure from motion. In: Proceedings of the 2014 IEEE International Conference on Robotics and Automation. Hong Kong, China: IEEE, 2014. 3090-3095
[62]	Malis E, Rives P. Robustness of image-based visual servoing with respect to depth distribution errors. In: Proceedings of the 2003 IEEE International Conference on Robotics and Automation. Taipei, China: IEEE, 2003. 1056-1061
[63]	Malis E, Mezouar Y, Rives P. Robustness of image-based visual servoing with a calibrated camera in the presence of uncertainties in the three-dimensional structure. IEEE Transactions on Robotics, 2010, 26(1): 112-120
[64]	Chaumette F. Potential problems of stability and convergence in image-based and position-based visual servoing. The Confluence of Vision and Control. London: Springer, 1998. 66-78
[65]	Slotine J J E, Li W P. On the adaptive control of robot manipulators. The International Journal of Robotics Research, 1987, 6(3): 49-59
[66]	Chen J, Dawson D M, Dixon W E, Behal A. Adaptive homography-based visual servo tracking for a fixed camera configuration with a camera-in-hand extension. IEEE Transactions on Control Systems Technology, 2005, 13(5): 814-825
[67]	Liu Ding, Wu Xiong-Jun, Yang Yan-Xi, Xin Jing. An improved self-calibration approach based on enhanced mutative scale chaos optimization algorithm for position-based visual servo. Acta Automatica Sinica, 2008, 34(6): 623-631(刘丁, 吴雄君, 杨延西, 辛菁. 基于改进变尺度混沌优化的自标定位置视觉伺服. 自动化学报, 2008, 34(6): 623-631)
[68]	Hu G Q, Gans N, Dixon W E. Adaptive visual servo control. Encyclopedia of Complexity and Systems Science. New York: Springer, 2009. 42-63
[69]	Liu Y H, Wang H S, Wang C Y, Lam K K. Uncalibrated visual servoing of robots using a depth-independent interaction matrix. IEEE Transactions on Robotics, 2006, 22(4): 804-817
[70]	Liang X W, Huang X H, Wang M, Zeng X J. Improved stability results for visual tracking of robotic manipulators based on the depth-independent interaction matrix. IEEE Transactions on Robotics, 2011, 27(2): 371-379
[71]	Fan Cai-Zhi, Song Bao-Quan, Liu Yun-Hui, Cai Xuan-Ping. Adaptive visual servoing of a small scale autonomous helicopter. Acta Automatica Sinica, 2010, 36(6): 894-900(范才智, 宋宝泉, 刘云辉, 蔡宣平. 微小无人直升机自适应视觉伺服. 自动化学报, 2010, 36(6): 894-900)
[72]	Liu Y H, Wang H S, Chen W D, Zhou D X. Adaptive visual servoing using common image features with unknown geometric parameters. Automatica, 2013, 49(8): 2453-2460
[73]	Wang H S, Liu Y H, Chen W D. Uncalibrated visual tracking control without visual velocity. IEEE Transactions on Control Systems Technology, 2010, 18(6): 1359-1370
[74]	Wang H L. Adaptive visual tracking for robotic systems without visual velocity measurement. Automatica, 2015, 55: 294-301
[75]	Lizarralde F, Leite A C, Hsu L, Costa R R. Adaptive visual servoing scheme free of image velocity measurement for uncertain robot manipulators. Automatica, 2013, 49(5): 1304-1309
[76]	Jagersand M, Fuentes O, Nelson R. Experimental evaluation of uncalibrated visual servoing for precision manipulation. In: Proceedings of the 1997 IEEE International Conference on Robotics and Automation. Albuquerque, NM: IEEE, 1997. 2874-2880
[77]	Piepmeier J A, McMurray G V, Lipkin H. Uncalibrated dynamic visual servoing. IEEE Transactions on Robotics and Automation, 2004, 20(1): 143-147
[78]	Lv X D, Huang X H. Fuzzy adaptive Kalman filtering based estimation of image Jacobian for uncalibrated visual servoing. In: Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. Beijing, China: IEEE, 2006. 2167-2172
[79]	Pari L, Sebastian J M, Traslosheros A, Angel L. A comparative study between analytic and estimated image Jacobian by using a stereoscopic system of cameras. In: Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. Taipei, China: IEEE, 2010. 6208-6215
[80]	Hu G Q, Gans N, Dixon W. Quaternion-based visual servo control in the presence of camera calibration error. International Journal of Robust and Nonlinear Control, 2010, 20(5): 489-503
[81]	Kim C S, Mo E J, Han S M, Jie M S, Lee K W. Robust visual servo control of robot manipulators with uncertain dynamics and camera parameters. International Journal of Control, Automation and Systems, 2010, 8(2): 308-313
[82]	Tsai C Y, Song K T. Visual tracking control of a wheeled mobile robot with system model and velocity quantization robustness. IEEE Transactions on Control Systems Technology, 2009, 17(3): 520-527
[83]	Tu Y W, Ho M T. Design and implementation of robust visual servoing control of an inverted pendulum with an FPGA-based image co-processor. Mechatronics, 2011, 21(7): 1170-1182
[84]	Tarbouriech S, Soures P. Image-based visual servo control design with multi-constraint satisfaction. Visual Servoing via Advanced Numerical Methods. London: Springer-Verlag, 2010. 275-294
[85]	Li You-Xin, Mao Zong-Yuan, Tian Lian-Fang. Visual servoing of 4DOF using image moments and neural network. Control Theory Applications, 2009, 26(10): 1162-1166(李优新, 毛宗源, 田联房. 基于图像矩与神经网络的机器人四自由度视觉伺服. 控制理论与应用, 2009, 26(10): 1162-1166)
[86]	Wang H B, Liu M. Design of robotic visual servo control based on neural network and genetic algorithm. International Journal of Automation and Computing, 2012, 9(1): 24-29
[87]	Siradjuddin I, Behera L, McGinnity T M, Coleman S. Image-based visual servoing of a 7-DOF robot manipulator using an adaptive distributed fuzzy PD controller. IEEE/ASME Transactions on Mechatronics, 2014, 19(2): 512-523
[88]	Bueno-Lpez M, Arteaga-Prez M A. Fuzzy vs nonfuzzy in 2D visual servoing for robot manipulators. International Journal of Advanced Robotic System, 2013, 10(108), DOI: 10.5772/55593
[89]	Jiang P, Unbehauen R. Robot visual servoing with iterative learning control. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 2002, 32(2): 281-287
[90]	Jia B X, Liu S, Liu Y. Visual trajectory tracking of industrial manipulator with iterative learning control. Industrial Robot: An International Journal, 2015, 42(1), 54-63
[91]	Jiang P, Bamforth L C A, Feng Z, Baruch J E, Chen Y Q. Indirect iterative learning control for a discrete visual servo without a camera-robot model. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2007, 37(4): 863-876
[92]	Kermorgant O, Chaumette F. Combining IBVS and PBVS to ensure the visibility constraint. In: Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). San Francisco, CA: IEEE, 2011. 2849-2854
[93]	Deng L F, Janabi-Sharifi F, Wilson W J. Hybrid motion control and planning strategies for visual servoing. IEEE Transactions on Industrial Electronics, 2005, 52(4): 1024-1040
[94]	Gans N R, Hutchinson S A. Stable visual servoing through hybrid switched-system control. IEEE Transactions on Robotics, 2007, 23(3): 530-540
[95]	Bhattacharya S, Murrieta-Cid R, Hutchinson S. Optimal paths for landmark-based navigation by differential-drive vehicles with field-of-view constraints. IEEE Transactions on Robotics, 2007, 23(1): 47-59
[96]	Lopez-Nicolas G, Gans N R, Bhattacharya S, Sagues C, Guerrero J J, Hutchinson S. Homography-based control scheme for mobile robots with nonholonomic and field-of-view constraints. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics, 2010, 40(4): 1115-1127
[97]	Branicky M S. Stability of hybrid systems: state of the art. In: Proceedings of the 1997 IEEE Conference on Decision and Control. San Diego, CA: IEEE, 1997. 120-125
[98]	Cao Z C, Yin L J, Fu Y L, LIU T L. Predictive control for visual servo stabilization of nonholonomic mobile robots. Acta Automatica Sinica, 2013, 39(8): 1238-1245
[99]	Allibert G, Courtial E, Chaumette F. Predictive control for constrained image-based visual servoing. IEEE Transactions on Robotics, 2010, 26(5): 933-939
[100]	Murao T, Kawai H, Fujita M. Visual motion observer-based stabilizing receding horizon control via obstacle avoidance navigation function. In: Proceedings of the 2012 IEEE International Conference on Control Applications. Dubrovnik, Croatia: IEEE, 2012. 903-909
[101]	Wang T T, Xie W F, Liu G D, Zhao Y M. Quasi-min-max model predictive control for image-based visual servoing with tensor product model transformation. Asian Journal of Control, 2014, DOI: 10.1002/asjc.871
[102]	Xi Yu-Geng, Li De-Wei, Lin Shu. Model predictive control status and challenges. Acta Automatica Sinica, 2013, 39(3): 222-236(席裕庚, 李德伟, 林姝. 模型预测控制--现状与挑战. 自动化学报, 2013, 39(3): 222-236)
[103]	Park J S, Chung M J. Path planning with uncalibrated stereo rig for image-based visual servoing under large pose discrepancy. IEEE Transactions on Robotics and Automation, 2003, 19(2): 250-258
[104]	Mezouar Y, Chaumette F. Optimal camera trajectory with image-based control. The International Journal of Robotics Research, 2003, 22(10-11): 781-803
[105]	Schramm F, Morel G. Ensuring visibility in calibration-free path planning for image-based visual servoing. IEEE Transactions on Robotics, 2006, 22(4): 848-854
[106]	Kyrki V, Kragic D, Christensen H I. New shortest-path approaches to visual servoing. In: Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems. Sendai, Japan: IEEE, 2004. 349-354
[107]	Allotta B, Fioravanti D. 3D motion planning for image-based visual servoing tasks. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation. Barcelona, Spain: IEEE, 2005. 2173-2178
[108]	Chesi G, Prattichizzo D, Vicino A. Straight line path-planning in visual servoing. Journal of Dynamic Systems, Measurement, and Control, 2007, 129(4): 541-543
[109]	Chesi G. Visual servoing path planning via homogeneous forms and LMI optimizations. IEEE Transactions on Robotics, 2009, 25(2): 281-291
[110]	Chesi G, Hung Y S. Global path-planning for constrained and optimal visual servoing. IEEE Transactions on Robotics, 2007, 23(5): 1050-1060
[111]	Chesi G, Shen T T. Conferring robustness to path-planning for image-based control. IEEE Transactions on Control Systems Technology, 2012, 20(4): 950-959
[112]	Tarabanis K, Tsai R Y, Kaul A. Computing occlusion-free viewpoints. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18(3): 279-292
[113]	Kazemi M, Gupta K, Mehrandezh M. Global path planning for robust visual servoing in complex environments. In: Proceedings of the 2009 IEEE International Conference on Robotics and Automation. Kobe, Japan: IEEE, 2009. 326-332
[114]	Baumann M, Leonard S, Croft E A, Little J J. Path planning for improved visibility using a probabilistic road map. IEEE Transactions on Robotics, 2010, 26(1): 195-200
[115]	Hayet J B, Esteves C, Murrieta-Cid R. A motion planner for maintaining landmark visibility with a differential drive robot. Algorithmic Foundation of Robotics VIII. Berlin: Springer-Verlag, 2009. 333-347
[116]	Salaris P, Fontanelli D, Pallottino L, Bicchi A. Shortest paths for a robot with nonholonomic and field-of-view constraints. IEEE Transactions on Robotics, 2010, 26(2): 269-281
[117]	Mezouar Y, Chaumette F. Path planning for robust image-based control. IEEE Transactions on Robotics and Automation, 2002, 18(4): 534-549
[118]	Chesi G, Vicino A. Visual servoing for large camera displacements. IEEE Transactions on Robotics, 2004, 20(4): 724-735
[119]	Zhang Xue-Bo, Fang Yong-Chun, Ma Bo-Jun. A PFM-based global convergence visual servo path planner. Acta Automatica Sinica, 2008, 34(10): 1250-1256(张雪波, 方勇纯, 马博军. 基于虚拟势场法的全局收敛视觉路径规划. 自动化学报, 2008, 34(10): 1250-1256)
[120]	Koditschek D E, Rimon E. Robot navigation functions on manifolds with boundary. Advances in Applied Mathematics, 1990, 11(4): 412-442
[121]	Cowan N J, Weingarten J D, Koditschek D E. Visual servoing via navigation functions. IEEE Transactions on Robotics and Automation, 2002, 18(4): 521-533
[122]	Chen J, Dawson D M, Dixon W E, Chitrakaran V K. Navigation function-based visual servo control. Automatica, 2007, 43(7): 1165-1177
[123]	Chen J, Dixon W E, Dawson D M, McIntyre M. Homography-based visual servo tracking control of a wheeled mobile robot. IEEE Transactions on Robotics, 2006, 22(2): 406-415
[124]	Diosi A, Segvic S, Remazeilles A, Chaumette F. Experimental evaluation of autonomous driving based on visual memory and image-based visual servoing. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(3): 870-883
[125]	Mehta S S, Jayaraman V, Burks T F, Dixon W E. Teach by zooming: aunified approach to visual servo control. Mechatronics, 2012, 22(4): 436-443
[126]	Mehta S S, Curtis J W. A geometric approach to visual servo control in the absence of reference image. In: Proceedings of the 2011 IEEE International Conference on Systems, Man, and Cybernetics. Anchorage, AK: IEEE, 2011. 3113-3118
[127]	Jia B X, Liu S. Homography-based visual predictive control of tracked mobile robot with field-of-view constraints. International Journal of Robotics and Automation, to be published
[128]	Li X, Cheah C C. Global task-space adaptive control of robot. Automatica, 2013, 49(1): 58-69
[129]	Karras G C, Loizou S G, Kyriakopoulos K J. Towards semi-autonomous operation of under-actuated underwater vehicles: sensor fusion, on-line identification and visual servo control. Autonomous Robots, 2011, 31(1): 67-86
[130]	Pasteau F, Krupa A, Babel M. Vision-based assistance for wheelchair navigation along corridors. In: Proceedings of the 2014 IEEE International Conference on Robotics and Automation. Hong Kong, China: IEEE, 2014. 4430-4435
[131]	Hager G D. Human-machine cooperative manipulation with vision-based motion constraints. Visual Servoing via Advanced Numerical Methods. London: Springer-Verlag, 2010. 55-70
[132]	Bachta W, Renaud P, Malis E, Hashimoto K, Gangloff J. Visual servoing for beating heart surgery. Visual Servoing via Advanced Numerical Methods. London: Springer-Verlag, 2010. 91-114
[133]	Li X, Cheah C C. Human-guided robotic manipulation: theory and experiments. In: Proceedings of the 2014 IEEE International Conference on Robotics and Automation. Hong Kong, China: IEEE, 2014. 4594-4599