Formation-based 3D mapping of micro aerial vehicles

Date of Publication


Document Type

Master's Thesis

Degree Name

Master of Science in Manufacturing Engineering


Gokongwei College of Engineering


Manufacturing Engineering and Management

Thesis Adviser

Elmer Jose P. Dadios

Defense Panel Chair

Argel A. Bandala

Defense Panel Member

Ryan Rhay P. Vicerra
Renann G. Baldovino
Jonathan R. Dungca


Unmanned Aerial Vehicle (UAV) has impacted a lot to the research community, particularly localization and mapping. There are a lot of advanced Laser Range Finders and RGBD cameras present in the market today that provide accurate 3D maps, though the concerns about these are their power requirement and weight. This means, smaller MAVs cannot be able to handle such kind of devices. The study explores the possibility of collaborative mapping from multiples of simple cameras to obtain an accurate map similar to that of the LRF and RGBD cameras. Formations were introduced on the swarm to help them map the environment better. The study also seeks to determine the effects in reconstruction when N number of MAVs, operating at varying heights, and di erent formations are used. COLMAP's Structure from Motion pipeline are used for the reconstruction and to provide the data such as the number of points, mean reprojection error, and the number of observations. The results shows that the formations significantly act the number of points, the value of the mean reprojection error, and the number of observations, whereas the v-formation has both a balance in number of points and value of mean reprojecton error. Moreover, an object detection algorithm is employed to determine the objects present within the periphery of the camera.

Abstract Format






Accession Number


Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

1 computer disc ; 4 3/4 in.


Micro air vehicles; Micro air vehicles--Control systems

This document is currently not available here.