Autonomous locative reasoning: an evidential approach

The authors describe efforts to develop an evidential approach to autonomous locative reasoning that shows promise of overcoming the computational burden of using Cartesian maps, and reduces the need to instrument environments. Perceptual cues were extracted from sonar and structured-light data and they were interpreted to infer the presence or absence of objects found local to the mobile platform. These objects, their spatial relationships, and knowledge of the previously known location were then used to infer the current location. The results of the experiments conducted so far suggest that evidential based locative reasoning techniques can help to bridge the technological gap left by current approaches.