|M.Sc Student||Evgeni Magid|
|Subject||Autonomous Robot Navigation|
|Department||Department of Applied Mathematics||Supervisors||Professor Daniel Keren|
|Full Professor Rivlin Ehud|
Motion planning is concerned with automatic planning of a collision-free path between initial and final configurations. The classical motion planning problem, termed the piano movers problem, is defined for complete a priori information about the obstacles in the environment. However, autonomous robots which operate in the real world, rather than in a structured workspace, cannot rely on a priori knowledge due to the dynamic and unpredictable nature of typical scenarios. In the situation when no map is available, the robot depends on its sensors in order to perceive the environment and plan accordingly. In this dissertation we present two new motion planning algorithms: the first algorithm deals with a piano movers problem, while the second solves a sensor-based motion planning problem.