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Infrastructure Planning for Unmanned Vehicle Navigation in Constrained Environments

Misra, Sohum
http://orcid.org/0000-0003-2381-3752
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1614079054152227

Abstract Details

2021, PhD, University of Cincinnati, Engineering and Applied Science: Aerospace Engineering.
Path planning algorithms for Unmanned Vehicles (UVs) that rely on Global Positioning System (GPS) for localization can be rendered ineffective upon disruption of GPS signals. Several authors have addressed this issue by considering an information rich environment. However, information may not be readily available and optimal feature (landmark) selection or placement is a challenge in itself. In this dissertation, the main focus is on addressing the problem of infrastructure planning to enable navigation of UVs through GPS degraded, and challenging areas. This work addresses incrementally challenging situations with the addition of constraints on information availability. Information availability depends upon existing infrastructure. Since infrastructure development has an associated cost, we seek the answer to the question: Is it possible to efficiently select/develop infrastructure while ensuring that all the constraints required for UV localization are satisfied? The answer to this question not only reduces infrastructure development cost but also improves the computational efficiency for estimation. Firstly, we developed techniques that would jointly reduce the cost of vehicle routing and infrastructure placement considering that we have the freedom to place landmarks in known locations using geometrical and graph connectivity based approaches. Next, we investigated further challenging scenarios to provide localization guarantees in feature deficient environments using (i) Relative, and (ii) Global frame-based navigation. For (i), conditions were developed for a group of UVs localizing themselves in a frame relative to a target without any additional requirement for infrastructure development. For the latter, we pursued several research directions to provide global guarantees. Finally, we developed a hybrid optimization solution to address the problem of providing uncertainty guarantees for an UV navigating in a dark, GPS constrained, and feature deficient environment, containing repetitive visual features, while ensuring a minimum number of landmarks are used and all the mission constraints are satisfied. In such a situation, Visual SLAM based techniques may fail to deliver the necessary localization performance. Our method utilizes range-based sensors as landmarks, that are carried by the vehicle and are deployed in the environment for localization. Our goal is to estimate and reduce the number of landmarks before the start of the mission, given some information about the environment. We validated the efficiency of our algorithms through extensive simulation and hardware testing.
Rajnikant Sharma, Ph.D. (Committee Chair)
Kelly Cohen, Ph.D. (Committee Member)
Manish Kumar, Ph.D. (Committee Member)
Ali Minai, Ph.D. (Committee Member)
Kaarthik Sundar, Ph.D. (Committee Member)
160 p.
Robots
Estimation; Optimization; Path Planning; Infrastructure Planning; Localization; Robotics

Recommended Citations

Citations

  • Misra, S. (2021). Infrastructure Planning for Unmanned Vehicle Navigation in Constrained Environments [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1614079054152227

    APA Style (7th edition)

  • Misra, Sohum. Infrastructure Planning for Unmanned Vehicle Navigation in Constrained Environments. 2021. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1614079054152227.

    MLA Style (8th edition)

  • Misra, Sohum. "Infrastructure Planning for Unmanned Vehicle Navigation in Constrained Environments." Doctoral dissertation, University of Cincinnati, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1614079054152227

    Chicago Manual of Style (17th edition)

ucin1614079054152227
197
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This open access ETD is published by University of Cincinnati and OhioLINK.