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Annotated Reconstruction of 3D Spaces Using Drones

Nair, Suraj and Ramachandran, Anshul and Kundzicz, Peter (2017) Annotated Reconstruction of 3D Spaces Using Drones. In: 2017 IEEE MIT Undergraduate Research Technology Conference (URTC). IEEE , Piscataway, NJ, pp. 1-5. ISBN 978-1-5386-2534-7.

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As the fields of robotics and drone technologies are continually advancing, the challenge of teaching these agents to learn and maneuver in the real world becomes increasingly important. A critical component of this is the ability for a robot to map and understand its surrounding unknown environment, both in terms of physical structure and object classification. In this project we tackle the challenge of mapping a 3D space with annotations using only 2D images acquired from a Parrot Drone. In order to make such a system operate efficiently in close to real time, we address a number challenges including (1) creating a optimized version of Faster RCNN that can operate on drone hardware while still being accurate, (2) developing a method to reconstruct 3D spaces from 2D images annotated with bounding boxes, and (3) using generated 3D annotations to complete drone motion planning for unknown space exploration.

Item Type:Book Section
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Additional Information:© 2017 IEEE.
Subject Keywords:Computer Vision, Robotics, Motion Planning
Record Number:CaltechAUTHORS:20171110-152713005
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Official Citation:S. Nair, A. Ramachandran and P. Kundzicz, "Annotated reconstruction of 3D spaces using drones," 2017 IEEE MIT Undergraduate Research Technology Conference (URTC), Cambridge, MA, USA, 2017, pp. 1-5. doi: 10.1109/URTC.2017.8284202. URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:83135
Deposited By: George Porter
Deposited On:10 Nov 2017 23:39
Last Modified:15 Nov 2021 19:55

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