Dissertation/Thesis Abstract

Toward Autonomous In-Flight Docking of Unmanned Multi-Rotor Aerial Vehicles
by Rocha, Ryan Alexander, M.S., University of California, Davis, 2020, 93; 27997949
Abstract (Summary)

The aim of this research is to develop a cost-effective, low-complexity system primarily using commercially-available parts to facilitate autonomous in-flight docking of unmanned, battery-powered multi-rotor aerial vehicles (MAV) using only onboard sensors. The robotic system presented herein consists of two MAVs, a visual servoing system and a docking mechanism. The docking MAV is responsible for performing the docking maneuver, while the carrier MAV receives the docking MAV. The docking mechanism consists of a rigid mast attached to the top of the carrier MAV. The camera used by the visual servoing system is mounted at the top of the mast. The frame of the docking MAV is ring-shaped to fit over the mast. The bottom of the ring-shaped frame of the docking MAV is surrounded with LED (light-emitting diode) fiducial markers. A simulation is constructed in order to model the system and develop the detection, tracking and navigation algorithms necessary for autonomous in-flight docking using visual servoing. The ability of the docking mechanism and visual servoing system to facilitate successful in-flight docking is demonstrated in simulation. Real-world flight tests are conducted to demonstrate the docking MAV's ability to hold its position over the center of the image of the camera with and without the visual servoing. The use of the visual servoing system reduces the root-mean-square error of the MAV's position hold by about 85% (0.64 m to 0.09 m) while also reducing its time spent outside of a desired horizontal radial limit of 0.11 m to 24% from 93%. These results suggest that this system is a viable approach to an in-flight docking system and should be explored further.

Indexing (document details)
Advisor: Robinson, Stephen
Commitee: Kong, Zhaodan, Joshi, Sanjay
School: University of California, Davis
Department: Mechanical and Aerospace Engineering
School Location: United States -- California
Source: MAI 82/2(E), Masters Abstracts International
Subjects: Robotics, Mechanical engineering, Aerospace engineering
Keywords: Autonomous, Docking, Drone, Multi-rotor, Robot, Vision
Publication Number: 27997949
ISBN: 9798664726312
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