Obstacle Discovery in Distributed Active Sensor Networks

Distributed active sensing is a new sensing paradigm, where active sensors as illuminating sources and passive sensors as receivers are distributed in a field, and collaboratively detect objects of interest. Obstacle discovery concerns with the problem of detecting the presence and determining the location of obstacles with many applications in robot navigation, object tracking, and surface and/or structure fatigue testing etc. In this paper, we study the fundamental properties of distributed active sensing networks (DASNs) in detecting and localizing obstacles. A novel notion of “exposure” is defined, which quantifies the dimension limitations in detectability. Using simple geometric constructs, we propose polynomial-time algorithms to compute the exposure and regions where the center of the obstacles may lie.