Cedric Cocaud and Amor Jnifene
Quadtree, mobile robots, navigation, mapping
This paper presents the implementation of an environment map- ping technique based on a probabilistic quadtree which records the location of static and dynamic obstacles, as well as the certainty over each obstacle’s estimated position. The quadtree-based map is updated online (i.e., near-real time) based on multi-sensor feeds originating from one to three X80 mobile robots operating simul- taneously. The probabilistic quadtree map is part of a guidance and navigation control (GNC) system which combines a genetic algorithm-based global path planner and a potential field local con- troller. The centralized map is shared by all mobile robots although each robot has an independent controller. Performance of the pro- posed method for this GNC system is demonstrated experimentally with the Dr. Robot’sTM wireless X80 mobile robots.
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