Perceptual ambiguity maps for robot localizability with range perception

A mobile robot equipped with 2D or 3D range sensors can move without changing its range readings if the perceived environment is poor in features. This is an ambiguous situation because a single perception can be associated with several robot poses. In consequence, robot localization capability is reduced. The problem we address is the quantification of this perceptual ambiguity as a property inherent to the system composed of the sensor and the static environment. Perceptual ambiguity is different from uncertainty of robot localization, although it is a cause of it. We propose an ambiguity model independent of the robot navigation system. It includes a probabilistic model of the indistinguishability of range readings, a generic range sensor model that supports laser and sonar sensors, and a generic range scanner model that supports any 2D or 3D range perception platform. Ambiguity is expressed in colour floor maps, which may be available before navigation starts, and where “bad localization” zones are easily detected. Experiments with virtual and real environments perceived from 2D laser and sonar scanners are presented, including the validation of the model with a real scans dataset. Results show how ambiguous zones are precisely determined, how to determine the optimum scanner orientation and aperture, and how to reduce the number of readings per scan for improving the robot’s computational load and navigation speed. © 2017 Elsevier Ltd