Topological Mapping with Weak Sensory Data

In this paper, we consider the exploration of topological environments by a robot with weak sensory capabilities. We assume only that the robot can recognize when it has reached a vertex, and can assign a cyclic ordering to the edges leaving a vertex with reference to the edge it arrived from. Given this limited sensing capability, and without the use of any markers or additional information, we will show that the construction of a topological map is still feasible. This is accomplished through both the exploration strategy which is designed to reveal model inconsistencies and by a search process that maintains a bounded set of believable world models throughout the exploration process. Plausible models are selected through the use of a ranking heuristic function based on the principle of Occam’s Razor. We conclude with numerical simulations demonstrating the performance of the algorithm.

Authors

• Gregory Dudek McGill University Samsung AI Center Montreal Mila - Quebec AI Institute

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