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Dissertation/Thesis Abstract

Energy Efficient Trajectory Planning of a Quadcopter for Infrastructure Inspection
by Ji, Ankyd, D.Engr., University of California, Davis, 2020, 84; 28149463
Abstract (Summary)

Infrastructure inspection is often considered a daunting task because it is dangerous to maneuver around aging bridges, dams, electric grids, buildings, and other facilities. In order to alleviate the dangers of infrastructure inspection, new technologies can be adapted into the process. This research focuses on a quadcopter vehicle’s capability as an inspector to complete the same inspection task as a human inspector. Quadcopters are versatile devices that can be flown by a human pilot or autonomously to gather aerial surveillance and inspection data while removing many of the risks of in person inspections. For inspecting civil infrastructures such as bridges, it is desirable to autonomously control these devices for inspection purposes. Since the use of LiDAR technology is commonly used to develop digital representation of such civil infrastructure assets, this thesis develops methods for quadcopter path planning and motion control using point cloud data of structures using LiDAR scanning. The LiDAR data will be filtered and segmented by various techniques developed in this research to improve the processing speed when using Artificial Potential Field (APF) methods for path planning. A camera is placed onboard the quadcopter and the camera parameters will act as trajectory constraints on the quadcopter platform. The various maneuvers a quadcopter can perform will be studied through equations of dynamics to find energy efficient methods of maneuvering. These energy efficiencies will also act as constraints alongside the camera constraints to build a motion planner. A traditional energy efficient path planner is also applied using the same LiDAR data as a comparison in processing time and energy saved. Multiple simulations were run and the results showed that the method outlined in this research can be twice as fast in processing with marginal losses in energy.

Indexing (document details)
Advisor: Ravani, Bahram
Commitee: Hess, Ron A., Vougioukas, Stavros G.
School: University of California, Davis
Department: Mechanical and Aerospace Engineering
School Location: United States -- California
Source: DAI-B 82/9(E), Dissertation Abstracts International
Subjects: Mechanical engineering, Aerospace engineering
Keywords: Energy efficiency, LiDAR, Path planning, Quadcopter, Infrastructure inspection
Publication Number: 28149463
ISBN: 9798582546115
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