【作者】 吴筱苏；

【导师】 肖本贤；

【作者基本信息】 合肥工业大学 ， 控制理论与控制工程， 2003， 硕士

【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。更多还原

【Abstract】 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.更多还原