| Summary: | The major problem addressed by this research is how to allow an autonomous vehicle to dynamically recognize changes in its environment, to map its environment, and alter its path to avoid obstacles while still reaching its goal point. The approach taken was to modify existing sonar functions in previous work, to better utilize sonars, and to perform many experiments to determine what data to expect from sonars while the vehicle is in motion. By applying the linear square fitting algorithm, the robot has the ability to map the objects within sensor range of an autonomous vehicle. The results are that, given an initial and goal point, the robot can proceed on a directed path, utilize its sonar sensor(s) used to detect obstacles, and when an obstacle is detected have the capability to dynamically compute a parallel path and smoothly alter its motion to the parallel path. The robot now has the capability to track the obstacle, and, once clear of the obstacle smoothly alter its motion to a path that will reach its goal point. The ability for the robot to combine smooth motion with obstacle avoidance has now been successfully programmed. Autonomous vehicle, Robot, Obstacle avoidance, Sonar sensing.
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