Monocular visual mapping for obstacle avoidance on UAVs

Daniel Magree, John G. Mooney, Eric N. Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

An unmanned aerial vehicle requires adequate knowledge of its surroundings in order to operate in close proximity to obstacles. UAVs also have strict payload and power constraints which limit the number and variety of sensors available to gather this information. It is desirable, therefore, to enable a UAV to gather information about potential obstacles or interesting landmarks using common and lightweight sensor systems. This paper presents a method of fast terrain mapping with a monocular camera. Features are extracted from camera images and used to update a sequential extended Kalman filter. The features locations are parameterized in inverse depth to enable fast depth convergence. Converged features are added to a persistent terrain map which can be used for obstacle avoidance and additional vehicle guidance. Simulation results and results from recorded flight test data are presented to validate the algorithm.

Original languageEnglish (US)
Title of host publication2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings
Pages471-479
Number of pages9
DOIs
StatePublished - 2013
Event2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Atlanta, GA, United States
Duration: May 28 2013May 28 2013

Publication series

Name2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings

Other

Other2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013
Country/TerritoryUnited States
CityAtlanta, GA
Period5/28/135/28/13

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

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