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Inverse Perspective Mapping Roll Angle Estimation for Motorcycles
Name
ICARCV_P2_2018_DAMON.pdf
Description
Accepted version
Size
646.74 KB
Format
Adobe PDF
Checksum (MD5)
ab3473b6582e62b08dadf2fa4551b50b
Author(s)
Damon, Pierre-Marie
Hadj-Abdelkader, Hicham
Arioui, Hichem
Youcef-Toumi, Kamal
Date Issued
November 2018
Journal
2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Damon, Pierre-Marie, Hadj-Abdelkader, Hicham, Arioui, Hichem and Youcef-Toumi, Kamal. 2018. "Inverse Perspective Mapping Roll Angle Estimation for Motorcycles." 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018.
Version
Author's final manuscript
Abstract
© 2018 IEEE. This paper presents an image-based approach to estimate the motorcycle roll angle. The algorithm estimates directly the absolute roll to the road plane by means of a basic monocular camera. This means that the estimated roll angle is not affected by the road bank which is often a problem for vehicle observation and control purposes. For each captured image, the algorithm uses a numeric roll loop based on some simple knowledge of the road geometry. For each iteration, a bird-eye-view of the road is generated with the inverse perspective mapping technique. Then, a road marker filter associated with the well-known clothoid model are used respectively to track the road separation lanes and approximate them with mathematical functions. Finally, the algorithm computes two distinct areas between the two-road separation lanes. Its performances are tested by means of the motorcycle simulator BikeSim. This approach is very promising since it does not require any vehicle or tire model and is free of restrictive assumptions on the dynamics.
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
10.1109/icarcv.2018.8581182
