In this paper, we introduce a novel algorithm for incorporating uncertainty into lookahead planning. Our algorithm searches through connected graphs with uncertain edge costs represented by known probability distributions. As a robot moves through the graph, the true edge costs of adjacent edges are revealed to the planner prior to...
This work proposes a technique for distributed multi-robot exploration that leverages novel methods of map inference. The inference technique uses observed map structure to infer unobserved map features. The team then coordinates to explore both the inferred and observed portions of the map. Individual robots select exploration poses by accounting...