Combined visual and inertial navigation for an unmanned aerial vehicle Conference Paper

abstract

• We describe an UAV navigation system which combines stereo visual odometry with inertial measurements from an IMU. Our approach fuses the motion estimates from both sensors in an extended Kalman filter to determine vehicle position and attitude. We present results using data from a robotic helicopter, in which the visual and inertial system produced a final position estimate within 1% of the measured GPS position, over a flight distance of more than 400 meters. Our results show that the combination of visual and inertial sensing reduced overall positioning error by nearly an order of magnitude compared to visual odometry alone. 2008 Springer-Verlag Berlin Heidelberg.

authors

• Saripalli, Srikanth

published proceedings

• FIELD AND SERVICE ROBOTICS: RESULTS OF THE 6TH INTERNATIONAL CONFERENCE

author list (cited authors)

• Kelly, J., Saripalli, S., & Sukhatme, G. S.

citation count

• 57

complete list of authors

• Kelly, Jonathan||Saripalli, Srikanth||Sukhatme, Gaurav S

publication date

• August 2008

publisher

• Springer Nature  Publisher

published in

• Springer Tracts in Advanced Robotics  Journal

keywords

• 40 Engineering
• 4001 Aerospace Engineering
• 4007 Control Engineering, Mechatronics And Robotics
• 46 Information And Computing Sciences
• 4602 Artificial Intelligence
• 4605 Data Management And Data Science
• Eye Disease And Disorders Of Vision

Digital Object Identifier (DOI)

• 10.1007/978-3-540-75404-6_24

International Standard Book Number (ISBN) 13

• 978-3-540-75403-9

start page

• 255

end page

• 264

volume

• 42

URL

• http://dx.doi.org/10.1007/978-3-540-75404-6_24