ICRA 2011 Paper Abstract


Paper WeA101.3

Milford, Michael J (Queensland University of Technology), Schill, Felix (The Australian National University), Corke, Peter (QUT), Mahony, Robert (Australian National University), Wyeth, Gordon (Queensland University of Technology)

Aerial SLAM with a Single Camera Using Visual Expectation

Scheduled for presentation during the Regular Sessions "Aerial Robotics III" (WeA101), Wednesday, May 11, 2011, 08:50−09:05, Room 3B

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on July 5, 2020

Keywords Aerial Robotics, SLAM, Mapping


Micro aerial vehicles (MAVs) are a rapidly growing area of research and development in robotics. For autonomous robot operations, localization has typically been calculated using GPS, external camera arrays, or onboard range or vision sensing. In cluttered indoor or outdoor environments, onboard sensing is the only viable option. In this paper we present an appearance-based approach to visual SLAM on a flying MAV using only low quality vision. Our approach consists of a visual place recognition algorithm that operates on 1000 pixel images, a lightweight visual odometry algorithm, and a visual expectation algorithm that improves the recall of place sequences and the precision with which they are recalled as the robot flies along a similar path. Using data gathered from outdoor datasets, we show that the system is able to perform visual recognition with low quality, intermittent visual sensory data. By combining the visual algorithms with the RatSLAM system, we also demonstrate how the algorithms enable successful SLAM.



Technical Content © IEEE Robotics & Automation Society

This site is protected by copyright and trademark laws under US and International law.
All rights reserved. © 2002-2020 PaperCept, Inc.
Page generated 2020-07-05  03:48:29 PST  Terms of use