| Mobile robot is required to traverse from start site to target site without man's interference in dynamic environment, so it must incorporate many functions such as environmental sense, dynamic decision, behavior control and execution. Mobile robot is often used as undersea robot, service robot, military robot, industry robot and space robot. In recent year, research on mobile robot has been scheduled in high technology development plan in many countries.In dynamic environment, circumstances will vary with robot's operation or change from time to time. Robot is required to detect what has happened in environment quickly and react in real-time. So main researches in the field of mobile robot are focus on multisensor integration and fusion, world model, control architecture, path planning and knowledge learning etc. It is a challenging and abstracting study to develop autonomous mobile robot suited for working in unknown environment.The research work in this paper includes high-level multisensor fusion, world model establishment, path planning control architecture and algorithm. The purpose of this dissertation is to propose a series of representation about features of environment and make them be useful for environmental information exchange, path planning and task planning respectively. In the same time, a hybrid control architect and some algorithms for path planning are put forward to improve performances in the aspect of robust, real-time, optimization, and adaptability in mobile system.The innovative work about this dissertation can be summarized as following aspects:1. Develop a multisensor data fusion experimental platform for mobile robot. In this platform, laser sensor is used for absolute location to remove cumulative error from odometer periodically to make a precise and real-time location system. Eight ultrasonic sensors are equipped to scan environment. Sensors are triggered or stopped by software set and maximum of range reading is also set by program. Data collection and data fusion are paralleled by a two-level distributed control system to increase reliability and get more timely information. Some experiments about navigation and collision avoidance for mobile robot are carried out by this platform.2. Present a statistical function by which gird map is created and updated according to ultrasonic range reading. This method can both find near obstacles and reduce error for far obstacles in gird map. Furthermore, an algorithm is proposed to convert gird map into polar map, and computation of this algorithm decreases as the number of obstacles encircling the robot increase and the distance between obstacles and robot is shortened. 3. Propose some data fusion methods to identify obstacle group, extract obstacle blink and compute environmental complexity index. Identifying obstacle group method can compress data below 20 percent of gird map while remaining features of environment for navigation. Especially it can find path between obstacles overlapped each other from the view of robot, which can't be realized by fuzzy plan, virtual force field or vector field histogram. The number of data of extracting obstacle blink method depends on blink features of obstacle on the side of robot and usually is larger than that of identifying obstacle group method. But this method keeps features of obstacle in detail so that central station can resume gird map by following received data. Environment complexity index is used for evaluating environmental complexity. It takes into account of the range occupied by obstacles in robot's 360° panorama, density of obstacle and the average distance between robot and obstacles. Features of path such as road length, degree of complexity and trend can be acquired by watching cumulative curve of Environment complexity index to provide dynamic information for task planning. These data fusion methods are so simple that functions of mobile robot system will be extended without cutting down performance of obstacle avoidance and path planning if little extra comp...
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