Abstract:
Path planning is one of the most critical aspects of developing and employing mobile robots. Apart from finding a suitable path, there is a great concern regarding quality of path as well. Among others, distance traversed from start point to goal is an important measure of quality and so is the safety of robot while adopting this path. Depending upon applications, the requirements from path planners are varying and sometimes conflicting, it is therefore a great deal of research is focused in this field including this one.
This research is an effort to develop a hybrid path planner by integrating visibility graph as global and artificial potential field as local path planner. The development of hybrid path planner by integration of global and local path planners focuses at exploiting their advantages and mitigating their shortcomings. This hybrid path planner, not only generates a near optimal path but also keeps robot safe as it ensures that throughout the course, it does not touches any obstacle or comes closer to it than a user defined distance. The work is also about making hybrid planner robust, flexible and reactive.
