AGV的视觉引导及其控制策略研究
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摘要
自动导向车(Automated Guided Vehicle,简称AGV)已经被广泛应用在制造业、医药、航天和军事等领域。AGV能够在具有一定地形特征的环境中顺利到达期望目的地或沿期望路径行驶。路径跟踪和路障躲避是任何一种AGV所必须具备的基本功能，这也是AGV导航的目的。AGV的导航能力和路径跟踪的精度主要受控制策略和实时控制性能的影响。
本文以两轮AGV为控制对象，采用高精度线阵CCD摄像头、高速DSP和超声波声纳构成AGV的视觉导航系统、运动控制系统和避障系统。着重研究AGV运动控制的视觉跟踪、图像处理、轨迹规划以及多电机控制等问题，力图开发出一种全新的基于机器视觉的智能AGV运动控制系统，该系统能引导AGV跟踪预定路径且能躲避路障。由于AGV的运行环境存在不确定性，难以建立环境模型，采用常规控制难以满足系统需要。本文采用模糊逻辑控制策略，它具有鲁棒性和容错性，可以提高AGV的实时控制性能。视觉传感器和超声波传感器感测环境特征，并把数据传给模糊控制器去控制AGV行驶。最后使用MATLAB模糊逻辑工具箱对模糊控制器进行了仿真。
Automated Guided Vehicles (AGV) have many potential applications in manufacturing, medicine, space and military fields etc. AGV can successfully reach its destination or move along a desired path in an environment characterized by a terrain. Path tracking and obstacle avoidance are two basic abilities of AGV, which aer also the goals of AGV guidance.
This thesis takes a two-wheels AGV as the control object. A high precision line scan CCD camera, high speed DSPs and ultrasonic sensors are used to build the vision guidance system, the motion control system and the obstacles avoidance system of AGV. The paper center is attached to discuss vision tracking, image processing, path planning and multi-motors controlling. This paper tries to develop a newly intelligent AGV motion control system based on machine vision, which can guide AGV to follow an expected path and avoid obstacles in the road. It is difficult to model AGV's running environment for many uncertainties during its operation , and conventional control methods cannot satisfy the system's demands. Fuzzy Logic control is adopted in this paper to improve AGV's real-time control performance due to its robustness and error-tolerance ability. The features of the environment is sensed by visual sensors and ultrasonic sensors ,then the information is transferred to a Fuzzy controller to guide the AGV. The
MATLAB Fuzzy Logic Toolbox is used finally to check the Fuzzy Logic controller.
本文以两轮AGV为控制对象，采用高精度线阵CCD摄像头、高速DSP和超声波声纳构成AGV的视觉导航系统、运动控制系统和避障系统。着重研究AGV运动控制的视觉跟踪、图像处理、轨迹规划以及多电机控制等问题，力图开发出一种全新的基于机器视觉的智能AGV运动控制系统，该系统能引导AGV跟踪预定路径且能躲避路障。由于AGV的运行环境存在不确定性，难以建立环境模型，采用常规控制难以满足系统需要。本文采用模糊逻辑控制策略，它具有鲁棒性和容错性，可以提高AGV的实时控制性能。视觉传感器和超声波传感器感测环境特征，并把数据传给模糊控制器去控制AGV行驶。最后使用MATLAB模糊逻辑工具箱对模糊控制器进行了仿真。
Automated Guided Vehicles (AGV) have many potential applications in manufacturing, medicine, space and military fields etc. AGV can successfully reach its destination or move along a desired path in an environment characterized by a terrain. Path tracking and obstacle avoidance are two basic abilities of AGV, which aer also the goals of AGV guidance.
This thesis takes a two-wheels AGV as the control object. A high precision line scan CCD camera, high speed DSPs and ultrasonic sensors are used to build the vision guidance system, the motion control system and the obstacles avoidance system of AGV. The paper center is attached to discuss vision tracking, image processing, path planning and multi-motors controlling. This paper tries to develop a newly intelligent AGV motion control system based on machine vision, which can guide AGV to follow an expected path and avoid obstacles in the road. It is difficult to model AGV's running environment for many uncertainties during its operation , and conventional control methods cannot satisfy the system's demands. Fuzzy Logic control is adopted in this paper to improve AGV's real-time control performance due to its robustness and error-tolerance ability. The features of the environment is sensed by visual sensors and ultrasonic sensors ,then the information is transferred to a Fuzzy controller to guide the AGV. The
MATLAB Fuzzy Logic Toolbox is used finally to check the Fuzzy Logic controller.
引文
[1] Graefe,V. Dynamic Vision Systems for Autonomous Mobile Robots.. Proc.IEEE/RSJ International Workshop on Intelligent Robots and Systems, IROS'89.Tsukuba,pp. 12-23,1989
[2] Choi, Jung W. Kwon, Soon H. Lee, Hae Y. Lee, Suk G.. Navigation Strategy of an Intelligent Mobile Robot Using Fuzzy logic, Proceedings of the 1998 IEEE International Conference on Fuzzy Systems, Part 1 of 2, Archorage, AK, USA,May 4-9, 1998, pp. 602-605
[3] Lei Mand Ghosh B K. Visually guided robotic tracking and grasping of a moving object[A]. Pro. the 32nd Conf. On Decision and Control [C], San Antonlo, Texas, 1993,851—856
[4] Kruse, E. Wahl, F.M.. Camera-based Monitoring System for Mobile Robot Guidance, Proceeding of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 2(of 3), Victoria, Can, Oct. 13-17, 1998, pp. 1248-1253
[5] C.V. Altrock et al.. Advanced fuzzy logic control technologies in automotive applications. Proceedings of 1st IEEE international Conference on Fuzzy Systems,pp.835-842,1992
[6] Samu,T.I..,Kelkar, N.and Hall,E. Fuzzy Logic System for Three Dimensional Line Following for a Mobile Robot, Proc. Adaptive Distributive Parallel Computing Symposium,Daytom,Oh,pp. 137-148
[7] Tayib Samu, Nikhil Kelkar, David Perdue, Mike Ruthemeyer, Bradley Matthews and Ernest Hall. "Line following using a two camera guidance system for a mobile robot," SPIE Conference 2904-39, Boston, MA, November 1996
[8] Kolli, Kalyan and Ernest L. Hall. Steering Control System for a Mobile Robot, Proceedings of SPIE-The international Society for Optical Engineering. v 3208, Society of Photo-Optical Instrumentation Engineers, Bellingham, WA, USA, 1997, pp. 162-169
[9] Scott Pawlikowski. Development of a Fuzzy Logic Speed and Steering Control System For an Autonomous Vehicle. M.S. thesis, University of Cincinnati, 1999
[10] Jin Cao. Vision Techniques and Autonomous Navigation for an Unmanned Mobile Robot. M.S. thesis, University of Cincinnati, 1999
[11] Ramesh Thyagarajan. A Motion Control Algorithm for Steering an AGV in an Outdoor Environment. M.S. thesis, the University of Cincinnati, 2000
[12] J. Borensteinl, H.R. Everett2, L. Feng3, and D. Wehe4. Integration of Sensors on a Mobile Robot. Invited paper for the Journal of Robotic Systems, Special Issue on Mobile Robots. Vol. 14 No. 4, pp.231-249
[13] S. Tho ngchai, S. Suks ak ulchai, D. M. Wilkes, and N. Sar kar. Sonar Behavior-Based Fuzzy Control for a Mobile Robot. Proceedings of the IEEE International Conference on Systems,Man and Cybernetics, Nashville, Tennessee, October 8-11,2000
[14] Borenstein, J. and Koren, Y., 1989. "Real-time Obstacle Avoidance for Fast Mobile Robots." IEEE Transactions on Systems, Man, and Cybernetics, Vol. 19, No. 5, Sept./Oct., pp. 1179-1187
[15] Mora, Thamar E. Sanchez, Edgar N.. Fuzzy Logic-based Real-time Navigation Controller for a Mobile Robot, Proceeding of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 1(of 3), Victoria, Can, Oct. 13-17, 1998, pp. 612-617
[16] Watanabe, Keigo Lzumi, Kiyotaka Tang, Jun Han, Fuhua. Rotational Control of an Omnidirectional Mobile Robot Using a Fuzzy Servo Controller, Advanced Robotics, Vol. 12, Issue 3, 1998, pp. 171-189
[17] Cao, Ming, Ernest Hall.. Fuzzy Logic Control for an Automated Guide Vehicle, University of Cincinnati, 1997
[18] JEFFREY S. WIT. Vector Pursuit Path Tracking for autonomous ground vehicles. Doctor of Philosophy thesis, University of Florida, 2000
[19] Lin, C. -H. and Wang, L.-L., Intelligent collision avoidance by fuzzy logic control, Robotics and Autonomous Systems, v20, n1, April 1997, p61-83.
[20] Fujimori, A., Nikiforuk, P. N. and Gupta, M. M., "Adaptive Navigation of Mobile Robots with Obstacle Avoidance," IEEE Transactions on Robotics and Automation, v13, n4, August 1997, p696-602.
[21] Yang, X., He, K., Guo, M. and Zhang, B., An Intelligent Predicitive Control Approach to Path Tracking Problem of Autonomous Mobile Robot, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, v4, San Diego, CA, 1998, p3301-3306.
[22] Sanchez, O, Ollero, A. and Heredia, G., Adaptive Fuzzy control for Automatic Path Tracking of Outdoor Mobile Robots. Application to Romeo 3R. IEEE International Conference on Fuzzy Systems, v1, Barcelona, Spain, 1997,p593-599.
[23] Baxter, J.W. and Bumby, J.R., Fuzzy Control of a Mobile Robotic Vehicle, Proceedings of the Institution of Mechanical Engineers. PartⅠ, Journal of Systems& Control Engineering, v209 n2 1995. P79-91.
[24] Ku, C.-H. and Tsai, W.-H., Smooth Vision-Based Autonomous Land Vehicle Navigation in Indoor Environments by Person Following Using Sequential Pattern Recognition, Journal of Robotic Systems, v16, n5, 1999, p249-262.
[25] Jiang, Z.-P. and Nijmeijer, H., "Tracking Control of Mobile Robots: A Case Study in Backstepping," Automatica, v33, n7, July 1997, p1393-1399.
[26] Lee, S. S. and Williams, J. H., "A fast tracking error control method for an autonomous mobile robot," Robotica, v11, 1993, p209-215.
[27] Wu, K.-H., Chen, C.-H. and Ko, J.-M., "Path Planning and Prototype Design of an AGV", Mathematical and Computer Modeling, v30, 1999, p147-167.
[28] Zhang, M., Peng, S. and Meng, Q., "Neural network and fuzzy logic techniques based collision avoidance for a mobile robot," Robotica, v15, 1997,p627-632.
[29] Yung, N. H. C. and Ye, C., "An Adaptive Fuzzy Approach to Obstacle Avoidance," Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, v4, San Diego, CA, 1998, p3418-3423.
[30] Li, W., Ma, C. and Wahl, F.M., "A neuro-fuzzy system architecture for behavior-based control of a mobile robot in unknown environments," Fuzzy Sets and Systems, v87, n2, April 1997, p133-140.
[31] Texas Instruments. CCD Image Sensors and Analog-to-Digital Conversion. January, 1993,SOCA010
[32] 李长贵，刘敬海，林幼娜，孙智勇．线阵CCD用于快速实时动态测量技术研究．应用光学，1998，第19卷，第4期，P36-39
[33] D. A. Lehotsky. Intelligent High Sensitivity CCD Line Scan Camera with Embedded Image Processing algorithms. DALSA INC 605 McMurray Road Waterloo, Ontario, N2V 2E9
[34] 孙振国，王军波，陈强，纪萌．新型智能球罐焊接机器人视觉传感器的研究．光学技术，2001，第27卷，第3期，P252-254
[35] 王地男．用CCD光电测量方法跟踪焊接筒体环行坡口的数控系统．光学精密工程，1996年，第4卷，第3期，P128-131
[36] 邓凌峰，刘丁，李奇．基于DSP的全数字直流模糊位置伺服控制系统．电气传动，2000，第2期，P33-36
[36] Implementation of PID and Deadbeat Controllers with the TMS320 Family, Texas Instruments. SPRA083
[37]雷江，陈幼平，夏泽中．基于DSP的主从运动控制系统的软件设计．机械与电子，2000，第6期，P32-34
[38]邓红辉．基于DSP的运动控制系统的研究．合肥工业大学硕士学位论文，2000
[39]杨延西，任海鹏，刘丁．交流伺服系统中DSP与上位机的通讯实现．电气传动，2000，第6期，P28-30
[40]程金林，周学才．国产MCT8000运动控制器的轨迹规划系统．机器人技术与应用，2001，第3期，P23-26
[41]周俊，姬长英。基于视觉导航的轮式运动机器人横向最优控制。机器人，2002，第24卷第3期，P209-212
[42]刘党辉，沈兰荪．DSP芯片及其在图像处理技术中的应用．测控技术，2001，第20卷，第5期，P16-19
[43]张忆蔚，段正华．CCD实时数据采集及动态观测软件．湖南大学学报，1998，第25卷，第5期，P182-186
[44]郑毅，韩正之，张钟俊．两轮驱动小车的反馈跟踪控制设计．上海交通大学学报，1994，第28卷，第4期，P58-62
[45]于慎波，张幼军，王燕玲，商向东．自动导向小车系统及其技术组成．沈阳工业大学学报，1998，第20卷，第4期，P46-49
[46]迟泽英，李坤宇，李武森，陈文建．高速DSP视频图像数字处理电路几个关键问题的研究．红外技术，2001，第23卷，第2期，P24-27
[47]蒋平，林靖，陈辉堂，王月鹃．机器人轨线跟踪的视觉与控制集成方法．自动化学报，1999，第25卷，第1期，P18-24
[48]雷鸣，王月鹃，蒋平．视觉引导的机器人轨线跟踪路径规划的一种新方法．机器人，1995，第17卷，第6期，P331-336
[49]林靖，陈辉堂，王月鹃，蒋平．机器人视觉伺服系统的研究．控制理论与应用，2000，第17卷，第4期，P476-481
[50]李庆中，顾伟康，叶秀清，项志宇．移动机器人路径跟踪的智能预瞄控制方法研究．机器人，2002，第24卷，第3期，P252-255
[51]张盛彬，王庆有，郭青．彩色线阵CCD用于物体尺寸精密测量的研究．光电子·激光，2001，第12卷，第11期，P1159-1161
[52]谈新权，梅哓英．高分辨率CCD图像传感器与CCD摄像机的性能评价．光学技术，1999，第1期，P70-72
[2] Choi, Jung W. Kwon, Soon H. Lee, Hae Y. Lee, Suk G.. Navigation Strategy of an Intelligent Mobile Robot Using Fuzzy logic, Proceedings of the 1998 IEEE International Conference on Fuzzy Systems, Part 1 of 2, Archorage, AK, USA,May 4-9, 1998, pp. 602-605
[3] Lei Mand Ghosh B K. Visually guided robotic tracking and grasping of a moving object[A]. Pro. the 32nd Conf. On Decision and Control [C], San Antonlo, Texas, 1993,851—856
[4] Kruse, E. Wahl, F.M.. Camera-based Monitoring System for Mobile Robot Guidance, Proceeding of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 2(of 3), Victoria, Can, Oct. 13-17, 1998, pp. 1248-1253
[5] C.V. Altrock et al.. Advanced fuzzy logic control technologies in automotive applications. Proceedings of 1st IEEE international Conference on Fuzzy Systems,pp.835-842,1992
[6] Samu,T.I..,Kelkar, N.and Hall,E. Fuzzy Logic System for Three Dimensional Line Following for a Mobile Robot, Proc. Adaptive Distributive Parallel Computing Symposium,Daytom,Oh,pp. 137-148
[7] Tayib Samu, Nikhil Kelkar, David Perdue, Mike Ruthemeyer, Bradley Matthews and Ernest Hall. "Line following using a two camera guidance system for a mobile robot," SPIE Conference 2904-39, Boston, MA, November 1996
[8] Kolli, Kalyan and Ernest L. Hall. Steering Control System for a Mobile Robot, Proceedings of SPIE-The international Society for Optical Engineering. v 3208, Society of Photo-Optical Instrumentation Engineers, Bellingham, WA, USA, 1997, pp. 162-169
[9] Scott Pawlikowski. Development of a Fuzzy Logic Speed and Steering Control System For an Autonomous Vehicle. M.S. thesis, University of Cincinnati, 1999
[10] Jin Cao. Vision Techniques and Autonomous Navigation for an Unmanned Mobile Robot. M.S. thesis, University of Cincinnati, 1999
[11] Ramesh Thyagarajan. A Motion Control Algorithm for Steering an AGV in an Outdoor Environment. M.S. thesis, the University of Cincinnati, 2000
[12] J. Borensteinl, H.R. Everett2, L. Feng3, and D. Wehe4. Integration of Sensors on a Mobile Robot. Invited paper for the Journal of Robotic Systems, Special Issue on Mobile Robots. Vol. 14 No. 4, pp.231-249
[13] S. Tho ngchai, S. Suks ak ulchai, D. M. Wilkes, and N. Sar kar. Sonar Behavior-Based Fuzzy Control for a Mobile Robot. Proceedings of the IEEE International Conference on Systems,Man and Cybernetics, Nashville, Tennessee, October 8-11,2000
[14] Borenstein, J. and Koren, Y., 1989. "Real-time Obstacle Avoidance for Fast Mobile Robots." IEEE Transactions on Systems, Man, and Cybernetics, Vol. 19, No. 5, Sept./Oct., pp. 1179-1187
[15] Mora, Thamar E. Sanchez, Edgar N.. Fuzzy Logic-based Real-time Navigation Controller for a Mobile Robot, Proceeding of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 1(of 3), Victoria, Can, Oct. 13-17, 1998, pp. 612-617
[16] Watanabe, Keigo Lzumi, Kiyotaka Tang, Jun Han, Fuhua. Rotational Control of an Omnidirectional Mobile Robot Using a Fuzzy Servo Controller, Advanced Robotics, Vol. 12, Issue 3, 1998, pp. 171-189
[17] Cao, Ming, Ernest Hall.. Fuzzy Logic Control for an Automated Guide Vehicle, University of Cincinnati, 1997
[18] JEFFREY S. WIT. Vector Pursuit Path Tracking for autonomous ground vehicles. Doctor of Philosophy thesis, University of Florida, 2000
[19] Lin, C. -H. and Wang, L.-L., Intelligent collision avoidance by fuzzy logic control, Robotics and Autonomous Systems, v20, n1, April 1997, p61-83.
[20] Fujimori, A., Nikiforuk, P. N. and Gupta, M. M., "Adaptive Navigation of Mobile Robots with Obstacle Avoidance," IEEE Transactions on Robotics and Automation, v13, n4, August 1997, p696-602.
[21] Yang, X., He, K., Guo, M. and Zhang, B., An Intelligent Predicitive Control Approach to Path Tracking Problem of Autonomous Mobile Robot, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, v4, San Diego, CA, 1998, p3301-3306.
[22] Sanchez, O, Ollero, A. and Heredia, G., Adaptive Fuzzy control for Automatic Path Tracking of Outdoor Mobile Robots. Application to Romeo 3R. IEEE International Conference on Fuzzy Systems, v1, Barcelona, Spain, 1997,p593-599.
[23] Baxter, J.W. and Bumby, J.R., Fuzzy Control of a Mobile Robotic Vehicle, Proceedings of the Institution of Mechanical Engineers. PartⅠ, Journal of Systems& Control Engineering, v209 n2 1995. P79-91.
[24] Ku, C.-H. and Tsai, W.-H., Smooth Vision-Based Autonomous Land Vehicle Navigation in Indoor Environments by Person Following Using Sequential Pattern Recognition, Journal of Robotic Systems, v16, n5, 1999, p249-262.
[25] Jiang, Z.-P. and Nijmeijer, H., "Tracking Control of Mobile Robots: A Case Study in Backstepping," Automatica, v33, n7, July 1997, p1393-1399.
[26] Lee, S. S. and Williams, J. H., "A fast tracking error control method for an autonomous mobile robot," Robotica, v11, 1993, p209-215.
[27] Wu, K.-H., Chen, C.-H. and Ko, J.-M., "Path Planning and Prototype Design of an AGV", Mathematical and Computer Modeling, v30, 1999, p147-167.
[28] Zhang, M., Peng, S. and Meng, Q., "Neural network and fuzzy logic techniques based collision avoidance for a mobile robot," Robotica, v15, 1997,p627-632.
[29] Yung, N. H. C. and Ye, C., "An Adaptive Fuzzy Approach to Obstacle Avoidance," Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, v4, San Diego, CA, 1998, p3418-3423.
[30] Li, W., Ma, C. and Wahl, F.M., "A neuro-fuzzy system architecture for behavior-based control of a mobile robot in unknown environments," Fuzzy Sets and Systems, v87, n2, April 1997, p133-140.
[31] Texas Instruments. CCD Image Sensors and Analog-to-Digital Conversion. January, 1993,SOCA010
[32] 李长贵，刘敬海，林幼娜，孙智勇．线阵CCD用于快速实时动态测量技术研究．应用光学，1998，第19卷，第4期，P36-39
[33] D. A. Lehotsky. Intelligent High Sensitivity CCD Line Scan Camera with Embedded Image Processing algorithms. DALSA INC 605 McMurray Road Waterloo, Ontario, N2V 2E9
[34] 孙振国，王军波，陈强，纪萌．新型智能球罐焊接机器人视觉传感器的研究．光学技术，2001，第27卷，第3期，P252-254
[35] 王地男．用CCD光电测量方法跟踪焊接筒体环行坡口的数控系统．光学精密工程，1996年，第4卷，第3期，P128-131
[36] 邓凌峰，刘丁，李奇．基于DSP的全数字直流模糊位置伺服控制系统．电气传动，2000，第2期，P33-36
[36] Implementation of PID and Deadbeat Controllers with the TMS320 Family, Texas Instruments. SPRA083
[37]雷江，陈幼平，夏泽中．基于DSP的主从运动控制系统的软件设计．机械与电子，2000，第6期，P32-34
[38]邓红辉．基于DSP的运动控制系统的研究．合肥工业大学硕士学位论文，2000
[39]杨延西，任海鹏，刘丁．交流伺服系统中DSP与上位机的通讯实现．电气传动，2000，第6期，P28-30
[40]程金林，周学才．国产MCT8000运动控制器的轨迹规划系统．机器人技术与应用，2001，第3期，P23-26
[41]周俊，姬长英。基于视觉导航的轮式运动机器人横向最优控制。机器人，2002，第24卷第3期，P209-212
[42]刘党辉，沈兰荪．DSP芯片及其在图像处理技术中的应用．测控技术，2001，第20卷，第5期，P16-19
[43]张忆蔚，段正华．CCD实时数据采集及动态观测软件．湖南大学学报，1998，第25卷，第5期，P182-186
[44]郑毅，韩正之，张钟俊．两轮驱动小车的反馈跟踪控制设计．上海交通大学学报，1994，第28卷，第4期，P58-62
[45]于慎波，张幼军，王燕玲，商向东．自动导向小车系统及其技术组成．沈阳工业大学学报，1998，第20卷，第4期，P46-49
[46]迟泽英，李坤宇，李武森，陈文建．高速DSP视频图像数字处理电路几个关键问题的研究．红外技术，2001，第23卷，第2期，P24-27
[47]蒋平，林靖，陈辉堂，王月鹃．机器人轨线跟踪的视觉与控制集成方法．自动化学报，1999，第25卷，第1期，P18-24
[48]雷鸣，王月鹃，蒋平．视觉引导的机器人轨线跟踪路径规划的一种新方法．机器人，1995，第17卷，第6期，P331-336
[49]林靖，陈辉堂，王月鹃，蒋平．机器人视觉伺服系统的研究．控制理论与应用，2000，第17卷，第4期，P476-481
[50]李庆中，顾伟康，叶秀清，项志宇．移动机器人路径跟踪的智能预瞄控制方法研究．机器人，2002，第24卷，第3期，P252-255
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