In this thesis, we propose algorithms designed for monitoring hazardous agents. Because hazardous environmental monitoring is either tedious or dangerous for human operators, we seek a fully automated robotic system that can help humans. However, there are still many challenges from hardware design to algorithm design that restrict robots to be applied to practical applications. Among these challenges, we are particularly interested in dealing with algorithmic challenges primarily caused by sensing and communication limitations of robots. We develop algorithms with provable guarantees that map and track hazards using a team of robots.
Our contributions are as follows. First, we address a situation where the number of hazardous agents is unknown and varies over time. We propose a search and tracking framework that can extract individual target tracks as well as estimate the number and the spatial density of targets. Second, we consider a team of robots tracking individual targets under limited bandwidth. We develop distributed algorithms that can find solutions in bounded amount of time. Third, we propose an algorithm for aerial robots that explores a translating hazardous plume of unknown size and shape. We present a recursive depth-first search-based algorithm that yields a constant competitive ratio for exploring a translating plume. Last, we take into account a heterogeneous team of robots to map and sample a translating plume. These contributions can be applied to a team of aerial robots and a robotic boat monitoring and sampling a translating hazardous plume over a lake. In this application, the aerial robots coordinate with each other to explore the plume and to inform the robotic boat while the robotic boat collects water samples for offline analysis. We demonstrate the performance of our algorithms through simulations and proof-of-concept field experiments for real-world environmental monitoring. / Doctor of Philosophy / Quick response to hazards is crucial as the hazards may put humans at risk and thorough removal of hazards may take a substantial amount of time. Our vision is that the introduction of a robotic solution would be beneficial for hazardous environmental monitoring. Not only the fact that humans can be released from dangerous or tedious tasks, but we also can take advantage of the robot's agile maneuverability and its precise sensing. However, the development on both hardware and software is not yet ripe to be able to deploy autonomous robots in real-world scenarios. Moreover, partial and uncertain information of hazards impose further challenges. In this these, we present various research problems addressing these challenges in hazardous environmental monitoring. Particularly, we are interested in overcoming challenges from the perspective of software by designing planning and decision-making algorithms for robots. We validate our proposed algorithms through extensive simulations and real-world experiments.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/95057 |
| Date | 24 October 2019 |
| Creators | Sung, Yoonchang |
| Contributors | Electrical Engineering, Tokekar, Pratap, Abbott, A. Lynn, Williams, Ryan K., Kekatos, Vasileios, Bansal, Manish |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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