【作者】 孙兰兰；

【导师】 毛建国；

【作者基本信息】 南京航空航天大学 ， 航空宇航科学与技术， 2007， 硕士

【摘要】 自主避障的能力是移动机器人智能化程度的重要指标,也是智能型车辆安全行驶的重要保障。自主避障算法是避障功能的灵魂所在,传统的控制算法通常依赖于被控对象精确的数学模型和完整全面的环境信息。当控制过程相对复杂,参数众多,环境信息不全,被控对象的数学模型难以确定时,避障效果往往不能令人满意。基于上述情况,本文进行了自主避障系统的研究和设计,该系统主要包含前端采集模块,中央处理模块,控制执行模块和被控对象四个部分。前端采集模块包含了超声波测距系统和伪距差分GPS定位系统,分别用于检测行驶过程中障碍物到被控对象的距离以及实现被控对象的自身定位,数据通过RS232串行接口传送给中央处理模块中的上位计算机;中央处理模块根据前端采集到的数据,采用相应的避障控制算法得出控制信号发送给控制执行模块;控制执行模块接收到控制信号后,通过触发无刷电机驱动转向机构,改变被控对象的行驶方向,从而实现避障。避障控制算法设计上引入了模糊控制理论,将避障行为划分为寻踪和避障两大行为模式,两种行为模式在相应条件下可相互切换。分别建立了两种模式的模糊控制器,对被控对象的转向角进行控制,通过转向角大小控制步长,来实现转弯过程中的自然减速。文中分析了几种典型的陷阱环境,通过设置虚拟目标点的方法进行陷阱避让,给出了具体实现方案。在Visual Basic集成开发环境下,设计了控制仿真平台用于仿真避障导航的控制过程,通过几种典型障碍物环境下的避障实验,验证了该算法具有很好的避障效果。前端采集模块中完成了基于AT89C51单片机的超声波测距系统的软、硬件设计,并进行了测距实验,结果表明该系统的测量误差为±2%。借助伪距差分GPS定位系统来实现自身的定位,以弥补单纯由传感器检测环境信息的不足。文中介绍了伪距差分GPS的定位原理,以及GPS信号的接收和处理的实现过程。控制执行机构选用了无刷电机和电动助力转向机构,被控对象采用了智能避障、越障概念车,组成了完整的自主避障系统,设置了真实情况下的不同障碍物环境,进行实车自主避障实验。实验的结果跟仿真的避障导航的控制过程吻合,也验证了该自主避障控制系统具有一定的现实意义。更多还原

【Abstract】 The ability to avoid the obstacles automatically measures the intellectualiztion of robots, as well as guarante safe travel for intelligent vehicles. Effective algorithm is the core of this ability. Traditional control algorithms always rely on accurate mathematical models of the controlled object and integrity environment information. So they are not quite satisfying, while the control process is relatively complex, or mathematical models are difficult to gain.During this thesis, the obstacle avoidance system was studied and designed. It could be divided into four parts: Information Gathering Module, Central Processing Module, Controlling Module and Controlled Object. Information Gathering Module was composed by ultrasonic distance measuring system and differential GPS system. They were used to measure the distances between obstacles and controlled object and to realize self-positioning. Datas were sent to upper compouter through serial interface and processed in Central Processing Module.Control signal was sent to Controlling Module. Brushless motor and steering component changed the steering angle in order to avoid obstacles.Fuzzy Logic Control theory was introduced in algorithm designing.The whole obstacle avoidance process was divided into two main behaivor patterns——goal seeking and obstacle avoidance.These two behavior patterns could be mutully shifted under certain conditions. Fuzzy controllers of each behaviour pattern were established. Step length was controlled by steering angle to decelerate during curving. Hypotesized aim method was used to avoid typical traps. The simulation platform of obstacle avoidance was developped and to testify the validity of the algorithm.Software and hardware design for ultrasonic distance measuring system were completed based on AT89C51 for Information Gathering Module. Measuring difference was computated to be±2%. Differential GPS was used to make up the insufficiency in circumstance detecting. Meanwhile, the theory of Global Positioning System, the process of signal receiving and processing were introduced.Brushless motor and Electricl Power Assisted Steering were chosen to compose the Implementing Module.The intelligent concept vehicle was taken as the controlled object to carry out experiments under real circumstances.The results of the experiments matched the simulation process and improved the significance of the whole system.更多还原