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Optimizing Safe Motion for Autonomous Vehicles

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Master's thesis

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There are two goals for autonomous vehicle navigation planning shortest path and safe path. These goals are often in conflict path safety is more important. Safety of the autonomous vehicles navigation is determined by the clearances between the vehicle and obstacles. Because a Voronoi boundary is the set of points locally maximizing the clearance from obstacles, safety is maximized on it. Therefore Voronoi Diagrams are suitable for motion planning of autonomous vehicles. We use the derivative of curvature k of the vehicle motion dkds as the only control variable for the vehicle where s is the length along the vehicle trajectory. Previous motion planning of the autonomous mobile robot Yamabico-11 at Naval Postgraduate School used a path tracking method. Before the mission began the vehicle was given a track to follow motion planning consisted of calculating the point on the track closest to the vehicle and calculating dk ds then steering the vehicle to get onto track. We propose a method of planning safe motions of the vehicle to calculate optimal dkds at each point directly from the information of the world without calculating the track to follow. This safe navigation algorithm is fundamentally different from the path tracking using a path specification. Additionally motion planning is simpler and faster than the path tracking method. The effectiveness of this steering function for vehicle motion control is demonstrated by algorithmic simulation and by use on the autonomous mobile robot Yamabico 11 at the Naval Postgraduate School.

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  • Land and Riverine Navigation and Guidance

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