This paper explores the problem of identifying the shapes of hazardous entities in R2 by a set S = {s1, s2, . . . , sk} of mobile sensors (autonomous robots). A hazardous entity, H, is a region that affects the operation of robots that either penetrate the area or come in contact with it. In this paper, we propose algorithms for searching a rectangular region for a stationary hazardous entity, where some a priori geometrical knowledge is given (e.g., edge size range), and if such an entity exists, then determine the area that it occupies. We explore entities that are convex in nature such as line segment, circles (discs), and simple convex shapes. The objectives are to minimize the distance travelled by the robots during the search phase, and to minimize the number of robots that are required to identify the region covered by the hazardous entity. The number of robots required to locate H is three or four robots when H is a line segment, two or three robots when H is a circle, and seven robots are sufficient when H is a triangle. Our results extend to n-vertex convex shapes and we show that 2n + 1 robots are sufficient to determine the coverage of H.

, ,
3rd IEEE International Conference on Robotic Computing, IRC 2019
School of Computer Science

Nussbaum, D, & Thoumy, S. (Stephanie). (2019). Identifying Hazardous Shapes in the Plane. In Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019 (pp. 271–276). doi:10.1109/IRC.2019.00051