智能移动机器人路径规划及仿真
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摘要
目前，智能移动机器人，无人自主车等领域的研究进入了应用的阶段，随着研究的深入，对移动机器人的自主导航能力，动态避障策略，避障时间等方面提出了更高的要求。地面智能机器人路径规划，是行驶在复杂，动态自然环境中的全自主机器人系统的重要环节，而地面智能机器人全地域全自主技术的研究，是当今国内外学术界面临的挑战性问题。
本论文首先对国内外机器人路径规划的研究现状，研究方法，及关键技术等进行了系统的归纳和总结，分析了其各自优点和不足之处。为本论文的研究工作奠定了重要的基础。然后，介绍了几种传统的移动机器人建模和路径规划的方法。接下来一章就是本文的主要算法，主要分为基于虚拟行走模块和旋转矢量算法的路径规划，基于视觉的道路跟踪算法和基于圆弧轨迹的四轮自主车行走模式，利用多种方法实现了移动机器人的路径规划，并对各个算法的原理进行了详细的推导和证明。在论文的最后一个部分，用vc和opengl分别对上述三个算法进行了仿真，并对整个仿真软件的界面，功能以及仿真环境进行了详细的介绍。实验结果有力地证明了算法的有效性。
总的来说，整篇论文介绍了一些路径规划算法，具有一定的实用价值。
At present time,intelligent automobile robot and autonomous land vehicle arrive at a new stage. With the development of research,high demands on the autonomous navigation ability, the method of dynamic avoidance obstacles and time of avoidance obstacles have also been put forward.The path planning of mobile robot is the important part of mobile robot system in which the robot move in the complex and dynamic environment.The research of technique about independence is a challenge to the domestic and foreign academe.
Firstly, the common used planning algorithm in the country and the broad , the researching situation and the key technologies are elaborated and summaried , analyzing advantages and defaults of algorithm which made an important basis for the research on mobile robot path planning in the thesis.Secondly, kinds of traditional methods about mobile robot modeling and path planning are recommended.In the following chapter,my innovational theories are elaborated,the theories include :the path-identify algorithm based on visition,the treading mode about autonomous land vehicle(ALV) based on circle locus, the path planning algorithm based on dummy moving module and method of rolling vector.The path planning of ALV is achieved by lots of algorithms and I have many details to explain and testify the methods.In the final chapter of this thesis,! have designed three simulation systems of mobile robot path planning based on visual C++ and opengl softwares.In this part ,the interfaces, the functions and the conditions of the simulation systems are recommended by lots of details. The simulation shows that the algorithm is feasible and efficient.
In conclusion,this thesis put forward a lot of unconventional and innovative algorithms,and have practicalities in some ways.
本论文首先对国内外机器人路径规划的研究现状，研究方法，及关键技术等进行了系统的归纳和总结，分析了其各自优点和不足之处。为本论文的研究工作奠定了重要的基础。然后，介绍了几种传统的移动机器人建模和路径规划的方法。接下来一章就是本文的主要算法，主要分为基于虚拟行走模块和旋转矢量算法的路径规划，基于视觉的道路跟踪算法和基于圆弧轨迹的四轮自主车行走模式，利用多种方法实现了移动机器人的路径规划，并对各个算法的原理进行了详细的推导和证明。在论文的最后一个部分，用vc和opengl分别对上述三个算法进行了仿真，并对整个仿真软件的界面，功能以及仿真环境进行了详细的介绍。实验结果有力地证明了算法的有效性。
总的来说，整篇论文介绍了一些路径规划算法，具有一定的实用价值。
At present time,intelligent automobile robot and autonomous land vehicle arrive at a new stage. With the development of research,high demands on the autonomous navigation ability, the method of dynamic avoidance obstacles and time of avoidance obstacles have also been put forward.The path planning of mobile robot is the important part of mobile robot system in which the robot move in the complex and dynamic environment.The research of technique about independence is a challenge to the domestic and foreign academe.
Firstly, the common used planning algorithm in the country and the broad , the researching situation and the key technologies are elaborated and summaried , analyzing advantages and defaults of algorithm which made an important basis for the research on mobile robot path planning in the thesis.Secondly, kinds of traditional methods about mobile robot modeling and path planning are recommended.In the following chapter,my innovational theories are elaborated,the theories include :the path-identify algorithm based on visition,the treading mode about autonomous land vehicle(ALV) based on circle locus, the path planning algorithm based on dummy moving module and method of rolling vector.The path planning of ALV is achieved by lots of algorithms and I have many details to explain and testify the methods.In the final chapter of this thesis,! have designed three simulation systems of mobile robot path planning based on visual C++ and opengl softwares.In this part ,the interfaces, the functions and the conditions of the simulation systems are recommended by lots of details. The simulation shows that the algorithm is feasible and efficient.
In conclusion,this thesis put forward a lot of unconventional and innovative algorithms,and have practicalities in some ways.
引文
[1] 李磊，叶涛，谭民，陈细军．移动机器人研究现状与未来．机器人．2002
[2] Trahanias P. Visual Recognition of Workspace Landmarks for Topological Navigation. Autonomous Robotics. 1999, 7(2): 143-158
[3] R A Brooks. Solving the Find-path problem by Good Representation of Free Space. IEEETrans on Sys Man andCybern. 1983, 13(3): 190—197
[4] 杨靖宇．多传感器集成与信息融合．机器人．2000，6
[5] R.Terry Dunlay and Steven B. Seida. Parallel Off-road Perception Processing On the Autonomous Land Vehicle. In:SPIE Vol. 1007 Mobile Robots Ⅲ. 1988:40-48
[6] 陈永芳，陈辉堂，蒋平．移动机器入全局最忧规划的研究．同济大学学报．1999(27)
[7] R.Terry Dunlay et al. Obstacle avoidance on roadways using range data. In:SPIE Vol.727 Mobile Robots. 1986:110-116
[8] 张颖，吴成东，于谦．基于遗传算法的机器人路径规划．沈阳建筑工程学院学报(自然科学版)．2002(18)
[9] Jean-Claude Latombe. Robot Motion Planning. Kluwer, Boston, MA. 1991
[10] Jed Lengvel, Mark Reichert, Bruce R. Donald, and Donald P. Greenberg. Real-time robot motion planning using rasterizing computer graphics hardware. SIGGRAPH'90. 24(4):327-335,1990.
[11] Robert J. Szczerba, Danny Z. then, and John J. Ohran Jr. A grid-based approach for finding conditional shortest paths in an unknown environment. Technical Report 94-34, University of Notre Dame, November 1994.
[12] Frencb, R.L, Historical Overview of Automobile Navigation Technology, IEEE Vehicular Technology Conference, 1986,350—358.
[13] Marques L, de Almeida, A T. App]ication of odor sensors in mobile robotics. In Autonomous Robotic Systems, Lecture Notes in Control and Information Sciences 236 1998:264-275
[14] Leigbty, R D. Terrain Navigation Concepts for Autonomous Vebicle, Proc of SPIE on Application of A1,1984,120—125.
[15] 李瑞峰，李伟招．基于多传感器信息融合的移动机器人路径规划．机电一
体化．2002，4
[16] Tsubuchi, T. ec, Map Assisted Vision System of Mobile Robots for Reckoning in a Building Environment, IEEE Int, Conf, Robotics and Automation, 1987,1978—1984.
[17] 孙羽，张汝波．神经网络在智能机器人导航系统中的应用研究．计算机工程．2002(28)
[18] 梁晓辉，吴威，赵沁平．大规模真实地形数据中的全局路径规划方法—基于遗传算法的研究．计算机研究与发展．2002，3
[19] 张汝波，熊烈彬等．基于势场法的水下机器在人全局路径规划研究．黑龙江自动化技术与应用．1995：30-33
[20] 陈永鸿，陈一秀．CAI动态全局规划．华侨大学学报：自然版 2000：319-324
[21] 叶媛媛，薛宏涛等．交互式智能体体系应用与研究．计算机与现代化2001：27-31
[22] 俞峥，李建勇．多智能体在交通系统中的应用．交通运输工程学报．2001(14)：0055-0057
[23] 国昌，张巧荣．移动机器人分层路径规划方法研究．哈尔滨工程大学学报2001：31-34
[24] 庄晓东，孟庆春．多障碍环境中基于增强式学习的势场优化和机器人路径规划．青岛海洋大学学报：自然科学版 2001(31)：937-942
[25] 梁晓辉，吴威等．大规模真实地形数据中的全局规划方法——基于遗传算法的研究．计算机研究与发展．2002(3)：301-306
[26] 唐平，杨宜民．动态二叉树表示环境的A算法及其在足球机器人路径规划的实现．中国工程科学．2002：50-53
[27] 艾海舟，张钹．基于拓扑的路径规划问题的图形解法．机器人．1990(5)：20-24。
[28] Olivier, J.L. et al, A Navigation Algorithm for an Intelligent Vehicle with a Laser Rangefinder, IEEE Int. Conf. Robotics and Automation, 1986,1145—1150.
[29] Steer, B. Trajectory planning for a Mobile Robot, Robotics Research, 8(1989),5,3—14.
[30] V. Boschian, A. Pruski. Grid Modeling of Robot Cell:A Memory-Efficient Approach. J of Intelligent and Robotics Systems, 1993, 8(1):201—209
[31] 马兆青，袁曾任．基于栅格方法的移动机器人实时导航和避障．机器人．1996，18(6)：344—348。
[32] 袁曾任，高明．在动态环境中移动机器人导航和避障的一种新方法．机器人．机器人．2000，22(2)：82—88。
[33] Kanayama Y, Yuta S I. Vehicle path specification by a sequence of straight lines IEEE J. on robotics and automation 43 1988: 265-276
[34] Triendl, E. Kriegman, D.j, Stereo Vision and Navigation within Buildings, IEEE Int. Conf. Robotics and Automation, 1987:1725—1730.
[35] Nelson W. Continuous curvature paths for automous vehicle Proc. IEEE Int. Conf. on robotics and automation 1989 1260-1264
[36] Wang Hong, Zhang bo Map based path planning and navigation
[37] Lozano-Perez T.,Welsey An algorithm for collision-free path among polyhedral obstacles Ass. Comput 22 1979:560-570
[38] Chien B.T.,Ling Zhang Planning collision-free path for robotic arm among obstacles IEEE Trans PAMI-6 1984 91-96
[39] 司秉玉，吕宗涛，徐心和．非完整自主车基于圆轨迹的道路避障．机器人．200325(2)
[40] McGiUem, C.D. et, Infra-red Location System for Navigation of Autonomous Vehicles, IEEE Int. Conf Robotics and Automation. 1988:1236—1238
[41] Jacobs P, Canny Planning smooth paths for mobile robots Proc. IEEE Int. Conf. On robotics and automation 1989: 2-7
[42] 董立志，孙茂相，朱枫，董再励，尹朝万．基于实时障碍物预测的机器人运动规划．机器人，2000，22(1)：12—16。
[43] Muir, P.R, Kinernatic Modeling of Wheeled Mobile Robots, Journal of Robotic Systems, 4(1987),2:281—340.
[44] 艾海舟张钹．移动机器人路径规划系统模式识别与人工智能．1991(3)
[45] Gex, w.T, Local Free Space Mapping and Path Guidance, IEEE Int. Conf. Robotics and Automation, 1987.424—431.
[46] 王人骅，唐新荣．软件技术基础．修订版．北京航天航空大学出版社，1994：pp286—289
[47] T. Lazano-Perez, M.A. Wesley. An Algorithm for Planning Collision-free Paths Among Polyhedral Obstacles. Communications of the ACM, 1979,560—570.
[48] T. Lazano-Perez. Automatic Planning of Manipulator Transfer Movements. IEEE Trans. on SMC, 1981,11(10):681—689
[49] 王洪．基于模型的移动机器人路径规划的研究．哈尔滨工业大学．1998(3)
[50] Ramiro Liscano, Allan Manz Using a blackboard to intrgrate multiple activaties and achieve strategic reasoning for mobile -robot navigation IEEE EXPERT April. 1995:24-36
[51] R Andrew Russell. Survey of Robotic Application for OdorSensing Technology. T he International Journal of Robotics Research. 2001,20(2):144-162
[52] Trahanias P. Visual Recognition of Workspace Landmarks for Topological Navigation. Autonomous Robotics, 1999,7(2):143-158
[53] Jie Huang, Tadawate Supaongprapa. A model-based sound localization system and its application to robot navigation. Robotics and Automous Systems. 1999(27):199-209
[54] Kanayama Y, Hartman B I. Smooth local path planning for autonomous vehicle Proc. IEEE Int. Conf. on robotics and automation 1989:1265-1270
[55] Schwartz. J.T. Planning, ceometry and complexity of robot motion Norwood New Jersey 1986:1-186
[56] Isaac Kaminer Trajectory tracking for autonomous vehicles:an integrated approach to guidance and control Journal of Guidance, Control and Dynamics 211 January-February, 1998 :29-32
[57] Sebastian Thrun, Arno B ucken, Wolfram Burgard, Dieter Fox, Map Learning and HighSpeed Navigation in RHINO.
[58] 何斌，马天予等．数字图像处理．北京：人民邮电出版社，2001
[59] 王宏，王学福．自然地形环境下移动机器人的一种路径规划方法．软件学报．1995(3)
[60] 王宏，张钹．基于地图的室外移动机器人路径规划与导航系统．机器人 1994(1)
[61] 赵春霞，唐振民，陆建峰，杨靖宇，刘传才．面向自主车辆的局部路径规划仿真系统．南京理工大学学报．2002(6)：570-574
[62] 张华祝，郝国防．无人驾驶车大漠争雄．2002
[63] Martial Herbert and Kanade T. Outdoor Scene Analysis Using Range Data. In:Proc. IEEE Conf. On Robotics and Automation. Apr. 1986:1426-1432
[64] 李晓敏．南京理工大学计算机系学位论文．2004
[65] 谢宏斌．动态环境下移动机器人路径规划的研究．江南大学学位论文．2003
[66] 庄健．基于视觉伺服智能移动机器人的研究．西安交通大学学位论文．2002
[2] Trahanias P. Visual Recognition of Workspace Landmarks for Topological Navigation. Autonomous Robotics. 1999, 7(2): 143-158
[3] R A Brooks. Solving the Find-path problem by Good Representation of Free Space. IEEETrans on Sys Man andCybern. 1983, 13(3): 190—197
[4] 杨靖宇．多传感器集成与信息融合．机器人．2000，6
[5] R.Terry Dunlay and Steven B. Seida. Parallel Off-road Perception Processing On the Autonomous Land Vehicle. In:SPIE Vol. 1007 Mobile Robots Ⅲ. 1988:40-48
[6] 陈永芳，陈辉堂，蒋平．移动机器入全局最忧规划的研究．同济大学学报．1999(27)
[7] R.Terry Dunlay et al. Obstacle avoidance on roadways using range data. In:SPIE Vol.727 Mobile Robots. 1986:110-116
[8] 张颖，吴成东，于谦．基于遗传算法的机器人路径规划．沈阳建筑工程学院学报(自然科学版)．2002(18)
[9] Jean-Claude Latombe. Robot Motion Planning. Kluwer, Boston, MA. 1991
[10] Jed Lengvel, Mark Reichert, Bruce R. Donald, and Donald P. Greenberg. Real-time robot motion planning using rasterizing computer graphics hardware. SIGGRAPH'90. 24(4):327-335,1990.
[11] Robert J. Szczerba, Danny Z. then, and John J. Ohran Jr. A grid-based approach for finding conditional shortest paths in an unknown environment. Technical Report 94-34, University of Notre Dame, November 1994.
[12] Frencb, R.L, Historical Overview of Automobile Navigation Technology, IEEE Vehicular Technology Conference, 1986,350—358.
[13] Marques L, de Almeida, A T. App]ication of odor sensors in mobile robotics. In Autonomous Robotic Systems, Lecture Notes in Control and Information Sciences 236 1998:264-275
[14] Leigbty, R D. Terrain Navigation Concepts for Autonomous Vebicle, Proc of SPIE on Application of A1,1984,120—125.
[15] 李瑞峰，李伟招．基于多传感器信息融合的移动机器人路径规划．机电一
体化．2002，4
[16] Tsubuchi, T. ec, Map Assisted Vision System of Mobile Robots for Reckoning in a Building Environment, IEEE Int, Conf, Robotics and Automation, 1987,1978—1984.
[17] 孙羽，张汝波．神经网络在智能机器人导航系统中的应用研究．计算机工程．2002(28)
[18] 梁晓辉，吴威，赵沁平．大规模真实地形数据中的全局路径规划方法—基于遗传算法的研究．计算机研究与发展．2002，3
[19] 张汝波，熊烈彬等．基于势场法的水下机器在人全局路径规划研究．黑龙江自动化技术与应用．1995：30-33
[20] 陈永鸿，陈一秀．CAI动态全局规划．华侨大学学报：自然版 2000：319-324
[21] 叶媛媛，薛宏涛等．交互式智能体体系应用与研究．计算机与现代化2001：27-31
[22] 俞峥，李建勇．多智能体在交通系统中的应用．交通运输工程学报．2001(14)：0055-0057
[23] 国昌，张巧荣．移动机器人分层路径规划方法研究．哈尔滨工程大学学报2001：31-34
[24] 庄晓东，孟庆春．多障碍环境中基于增强式学习的势场优化和机器人路径规划．青岛海洋大学学报：自然科学版 2001(31)：937-942
[25] 梁晓辉，吴威等．大规模真实地形数据中的全局规划方法——基于遗传算法的研究．计算机研究与发展．2002(3)：301-306
[26] 唐平，杨宜民．动态二叉树表示环境的A算法及其在足球机器人路径规划的实现．中国工程科学．2002：50-53
[27] 艾海舟，张钹．基于拓扑的路径规划问题的图形解法．机器人．1990(5)：20-24。
[28] Olivier, J.L. et al, A Navigation Algorithm for an Intelligent Vehicle with a Laser Rangefinder, IEEE Int. Conf. Robotics and Automation, 1986,1145—1150.
[29] Steer, B. Trajectory planning for a Mobile Robot, Robotics Research, 8(1989),5,3—14.
[30] V. Boschian, A. Pruski. Grid Modeling of Robot Cell:A Memory-Efficient Approach. J of Intelligent and Robotics Systems, 1993, 8(1):201—209
[31] 马兆青，袁曾任．基于栅格方法的移动机器人实时导航和避障．机器人．1996，18(6)：344—348。
[32] 袁曾任，高明．在动态环境中移动机器人导航和避障的一种新方法．机器人．机器人．2000，22(2)：82—88。
[33] Kanayama Y, Yuta S I. Vehicle path specification by a sequence of straight lines IEEE J. on robotics and automation 43 1988: 265-276
[34] Triendl, E. Kriegman, D.j, Stereo Vision and Navigation within Buildings, IEEE Int. Conf. Robotics and Automation, 1987:1725—1730.
[35] Nelson W. Continuous curvature paths for automous vehicle Proc. IEEE Int. Conf. on robotics and automation 1989 1260-1264
[36] Wang Hong, Zhang bo Map based path planning and navigation
[37] Lozano-Perez T.,Welsey An algorithm for collision-free path among polyhedral obstacles Ass. Comput 22 1979:560-570
[38] Chien B.T.,Ling Zhang Planning collision-free path for robotic arm among obstacles IEEE Trans PAMI-6 1984 91-96
[39] 司秉玉，吕宗涛，徐心和．非完整自主车基于圆轨迹的道路避障．机器人．200325(2)
[40] McGiUem, C.D. et, Infra-red Location System for Navigation of Autonomous Vehicles, IEEE Int. Conf Robotics and Automation. 1988:1236—1238
[41] Jacobs P, Canny Planning smooth paths for mobile robots Proc. IEEE Int. Conf. On robotics and automation 1989: 2-7
[42] 董立志，孙茂相，朱枫，董再励，尹朝万．基于实时障碍物预测的机器人运动规划．机器人，2000，22(1)：12—16。
[43] Muir, P.R, Kinernatic Modeling of Wheeled Mobile Robots, Journal of Robotic Systems, 4(1987),2:281—340.
[44] 艾海舟张钹．移动机器人路径规划系统模式识别与人工智能．1991(3)
[45] Gex, w.T, Local Free Space Mapping and Path Guidance, IEEE Int. Conf. Robotics and Automation, 1987.424—431.
[46] 王人骅，唐新荣．软件技术基础．修订版．北京航天航空大学出版社，1994：pp286—289
[47] T. Lazano-Perez, M.A. Wesley. An Algorithm for Planning Collision-free Paths Among Polyhedral Obstacles. Communications of the ACM, 1979,560—570.
[48] T. Lazano-Perez. Automatic Planning of Manipulator Transfer Movements. IEEE Trans. on SMC, 1981,11(10):681—689
[49] 王洪．基于模型的移动机器人路径规划的研究．哈尔滨工业大学．1998(3)
[50] Ramiro Liscano, Allan Manz Using a blackboard to intrgrate multiple activaties and achieve strategic reasoning for mobile -robot navigation IEEE EXPERT April. 1995:24-36
[51] R Andrew Russell. Survey of Robotic Application for OdorSensing Technology. T he International Journal of Robotics Research. 2001,20(2):144-162
[52] Trahanias P. Visual Recognition of Workspace Landmarks for Topological Navigation. Autonomous Robotics, 1999,7(2):143-158
[53] Jie Huang, Tadawate Supaongprapa. A model-based sound localization system and its application to robot navigation. Robotics and Automous Systems. 1999(27):199-209
[54] Kanayama Y, Hartman B I. Smooth local path planning for autonomous vehicle Proc. IEEE Int. Conf. on robotics and automation 1989:1265-1270
[55] Schwartz. J.T. Planning, ceometry and complexity of robot motion Norwood New Jersey 1986:1-186
[56] Isaac Kaminer Trajectory tracking for autonomous vehicles:an integrated approach to guidance and control Journal of Guidance, Control and Dynamics 211 January-February, 1998 :29-32
[57] Sebastian Thrun, Arno B ucken, Wolfram Burgard, Dieter Fox, Map Learning and HighSpeed Navigation in RHINO.
[58] 何斌，马天予等．数字图像处理．北京：人民邮电出版社，2001
[59] 王宏，王学福．自然地形环境下移动机器人的一种路径规划方法．软件学报．1995(3)
[60] 王宏，张钹．基于地图的室外移动机器人路径规划与导航系统．机器人 1994(1)
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