Tracking and Following a Moving Person Onboard a Small Pocket Drone

Title

Tracking and Following a Moving Person Onboard a Small Pocket Drone

 Author

Duro, T.

Contributor

De Croon, G. (mentor)
De Wagter, C (mentor)
Meertens, R. (mentor)

Faculty

Aerospace Engineering

 Date

2016-08-25

 Abstract

This paper presents a vision based strategy, designed to work fully onboard a small pocket drone, for autonomously tracking and following a person. Flying a drone is not an easy task, usually requiring a trained pilot, with the presented system it is possible to use a drone for filming or taking pictures from previously inaccessible places without the need for a person controlling the aircraft. Such framework is comprised by two main components, a tracker and a control system. The tracker has the function of estimating the position of the person that is being followed, while the control system gets the drone near that person. Limited by payload weight, power consumption and processing power the system results in a delicate balance between these constraints. The main contributions of this paper are the comparison between two state-of-the-art visual trackers running on paparazzi, Struck and KCF, as well as the control system that uses the tracker’s output location to perform the person following task. Then a new tracker is developed to be as computationally light as possible so that it can run onboard a small pocket drone, based on HOG feature extraction, it uses logistic regression to train a detector on the appearance of a person.

 To reference this document use:

http://resolver.tudelft.nl/uuid:58a4c285-e3b6-4bf0-b885-2908077e9b02

 Part of collection

Student theses

 Document type

master thesis

 Rights

(c) 2016 Duro, T.
Files
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