Modeling and simulating a path planning and obstacle avoidance algorithm for an autonomous robotic vehicle

Path planning in robotics deals with developing the logic for the navigation of a robot. The implementation details of most previous algorithms are proprietary to specific organizations. The requirement of a customized strategy for collision free and concerted navigation of an all-terrain vehicle (ATV) led to the activities of this research. As a part of this research an algorithm has been developed and visually simulated. The algorithm is evolutionary and capable of path planning for ATVs in the presence of completely known and newly-discovered obstacles. This algorithm helps the ATV model to maneuver in an open field in a specific pattern and avoid obstacles, if any, along its path. The algorithm is implemented and simulated using C and WINAPI. As a result, given the data of known obstacles and the field, the virtually-modeled ATV can maneuver in a systematic and optimum manner towards its goal by avoiding all the obstacles in its path.