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Detecting unexpected obstacles and avoiding collisions is an important task for any autonomous mobile system. This article describes GANESHA (Grid based Approach for Navigation by Evidence Storage and Histogram Analysis), a system using sonar that we implemented for the autonomous land vehicle Navlab. The general hardware configuration of the system is shown, followed by a description of how the system builds a local grid map of its environment. The information collected in the map can then be used for a variety of applications in vehicle navigation like collision avoidance, feature tracking and parking. An algorithm was implemented that can track a static feature such as a rail, wall or an array of parked cars and use this information to drive the vehicle. Methods for filtering the raw data and generating the steering commands are discussed and the implementation for collision avoidance, parallel parking and its integration with other vehicle systems is described.

Range sensor based outdoor vehicle Navigation, collision avoidance and parallel parking