L. Muñoz-Gomez, M. Alencastre-Miranda, and R. Swain-Oropeza (Mexico)
Mobile robotics, motion planning, multi-robot mapping, segmentation.
This paper presents a mapping system with multiple robots for indoor environment. Each robot uses its own laser range finder (LRF) as sensor and builds a local map (segment-based), these maps are sent to a server that joints the partial maps and then generates a global map. The robots relative positions are known in advance at the beginning; during the mapping process each robot has its own information without knowing about each other. The next possible position that each robot chooses for taking a new reading, is selected considering the free edges obtained from the segmented range points. Each time a new reading is taken, segments are matched using the Hausdorff distance in order to find two or more segments that can be fused in a single one. Two different motion planning approaches for reaching the next position during the exploration have been implemented: Markov Decision Process (MDP) and Roadmaps considering part of the environment already known (Visibility roadmap, probabilistic roadmap and visibility probabilistic roadmap). Results using simulations and real robots are presented.
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