Study On Path Planning Of Robot Based On Artificial Potential Field

The technology of mobile robot is an important branch of robotics. It's an advanced technology which has expansive application fields. From industrial manufacture to military spy, services, nuclear industry, aviation and spaceflight, service industry, medical instrument, gene engineering, etc, mobile robot has great development space in all of these fields. Robotics, as a multi-subject syncretized high-tech science, is certainly difficult to research. For the diversity and complexity of the environment, path planning has being an important aspect in the mobile robotic research field and also a crucial technology to intelligentize the robot. Path planning problem is one of the most basic and pivotal aspects in the research of mobile robot. Its task is to solve the problem of how to move in the environment for robot. Path planning is not an independent aspect in the research of mobile robot. It is relative with many other aspects, such as sense system, communication system and the rules of collaboration. This thesis mainly does the research on the path planning problem for mobile robot; the results of simulation demonstrate the validity of proposed theory and methods. The mainly comment and achievements of the thesis are as follows:First of all, this thesis analyses the status and development trend is elaborated and summarized of intelligent mobile robot at home and abroad. It is introduced to the navigation technology of the mobile robot. The necessary technology of modeling and sensing of mobile robot is summarized. In addition, the existed path planning methods are sorted and summarized. All these make a good preparation for the research on the path planning problem of mobile robot.Second, It analyses the classical Artificial Potential Field of path planning principle on the basis of describing the mobile robot control system. This thesis solves a number of methods flawed of traditional artificial potential field and optimizes the algorithm. It adopts improved repulsive potential function for Goals Nonreachable with Obstacles Nearby of potential field, the new repulsive potential function considers the relative distance between the robot and the goal which ensures the goal is the global minimum of the whole potential field, so the robot can reach the goal freely. This thesis also proposes a method of adding mid-goal point for trap situation duo to the local stability problem. The mobile robot can reach the goal freely through this method. The effectiveness of this method is verified by simulation results.In the end, basing Grandar's AS-R mobile robot platform, experiment is carried using backstepping method and trajectory tracking curve is analyzed.