Thanks to advances in miniaturization, computing power, reliable sensors, and battery life, mobile robots are increasingly being used for a wide variety of environmental monitoring tasks. No longer confined to factory floors or controlled environments, robots for remote sensing in dangerous or hard-to-reach environments could provide the same scalability, precision, and reliability to environmental monitoring as they did to industrial applications. To enable this kind of long-term, reliable, autonomous mobile sensor deployment, algorithms which can ensure that the robots achieve their sensing tasks are required. In the first part of the thesis, we study the problem of using one or more mobile robots equipped with bearing sensors to locate a stationary target in minimum time. The problem requires optimizing the measurement locations of the robots to gather the required information about the target's location. In addition, when multiple robots collaborate, we include communication constraints in the path planning objective. Two formulations for this problem are studied. First, we study the offline problem of finding measurement trajectories when the true target location is known. Second, we study the online version and show how to adapt the offline solution to the situation when the target location is not known, while preserving the quality guarantees of the offline solution. In the second part of the thesis, we study the problem of locating multiple stationary targets using a single mobile robot. We formulate a novel coverage problem and provide two main results. We first study the problem of initializing consistent estimate of the targets' locations. These initial estimates are used to seed an active localization algorithm which is shown to localize the targets quickly. In a second formulation, we assume that the targets are within a set of polygonal regions, but have no further information about the distribution or number of targets in the environment. An algorithm is provided which can choose measurement locations to localize all the targets to within desired precision in near optimal time. In the third part of the thesis, we study the problem of using bearing information to track and capture a moving target. We present two formulations based on pursuit-evasion games. In the open plane, the objective is for a mobile robot to minimize the distance to a maneuvering target when only uncertain bearing information is available to the robot. Then, we study the problem of capturing the maneuvering target in a closed environment by moving close to it. We show that the size of the environment relative to the sensing noise determines if this is possible. HASH(0x7febe3ca4040) In addition to theoretical results, we present field studies of using one or more mobile robots to detect radio transmitters using these results. We show that the algorithms presented are suitable for use in monitoring invasive fish.
University of Minnesota Ph.D. dissertation. September 2015. Major: Computer Science. Advisor: Ibrahim Isler. 1 computer file (PDF); xi, 172 pages.
Vander Hook, Joshua.
Active Target Localization and Tracking with Application to Robotic Environmental Monitoring.
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