Vander Hook, JoshuaTokekar, Pratap2020-09-022020-09-022013-04-08https://hdl.handle.net/11299/215915We study the problem of locating a stationary target using two robots equipped with bearing sensors. The goal is to reduce the uncertainty in the target's location to a value below a given threshold in minimum time. Our cost formulation explicitly models time spent in traveling as well as taking measurements. Further, the robots are subject to distance-based communication constraints. We first study properties of an optimal strategy which has access to the target's true location. It turns out that under certain circumstances, the optimal algorithm will break communication to take measurements and rendezvous to merge them. Using these insights, we design an online strategy (which does not have access to the target's true location) and show that the strategy can locate the target up to a desired uncertainty level at near-optimal cost. The results are applicable to other bearing sensors with non-zero measurement cost, such as pan- tilt cameras. In addition to theoretical analysis, we validate the algorithm in simulations and field experiments performed using autonomous surface vehicles. This full version includes proofs which are not included in the conference version.en-USReport