Local perception maps for autonomous robot navigation

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Abstract
This paper describes a mobile robotics system that was implemented and is capable of building instantaneous representations of the free space available, and use those representations to perform navigation. The free space representations are done by means of perception maps specially designed to hold and combine ultrasonic data. The maps are built by neural network appropriately trained to minimise undesired ranging errors due to specular reflections that is achieved by taking advantage of the redundancy of sensorial data. The concept of local navigation is developed as a new navigation approach, and is based on full independence on the environment, relying purely on sensorial perception. Local motion is generated according to simple generic behaviour descriptions: the local navigation strategies. The system which was implemented guarantees a safe local motion throughout the environment, requiring no a priori information nor any pre-defined path to follow. An adequate navigation architecture integrates the local navigation module within a framework of other several modules for more complete navigation tasks. The results obtained are quite promising in pointing the way to a truly autonomous system.

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