Filtering Reading Sets for Improved Occupancy Grid Mapping

The performance of an autonomous mobile robot in acquiring a meaningful spatial model of its operating environment depends greatly on the accuracy of its perceptual capabilities. A key challenge in the field arises from handling sensor measurements and in particular the handling of measurement noise. The current prevailing approach used when attempting to deal with the problem of noisy readings is to tune the sensory model to explicitly accommodate this sensory noise. An alternative approach, however, is to consider the issue of noisy readings as a separate problem and address accordingly. In this paper such an approach is outlined. Experimental evaluation illustrate the associated improvement in map quality across a number of established paradigms.