Abstract
Estimating the 3D pose of objects is an important problem in vision-based robotics. Kalman filters are commonly used as efficient solutions to this problem. However, the performance of these filters deteriorates when system’s noise statistics are not known a priori. This work proposes an adaptive scheme based on particle swarm optimization (PSO) to adjust the measurement noise covariance of the filter. The experimental results confirm the effectiveness of the proposed adaptive solution for Kalman-based pose estimation with uncertain noise statistics.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
K. Fathian, J. Jin, S.G. Wee, D.H. Lee, Y.G. Kim, N.R. Gans, Camera relative pose estimation for visual servoing using quaternions, Robot. Auton. Syst. (2018)
E. Marchand, H. Uchiyama, F. Spindler, Pose estimation for augmented reality: a hands-on survey. IEEE Trans. Vis. Comput. Graph. 22(12), 2633–2651 (2016)
A. Assa, F. Janabi-Sharifi, Virtual visual servoing for multicamera pose estimation. IEEE/ASME Trans. Mechatron. 20(2), 789–798 (2015)
A. Tejani, R. Kouskouridas, A. Doumanoglou, D. Tang, T.K. Kim, Latent-class Hough forests for 6 DoF object pose estimation. IEEE Trans. Pattern Anal. Mach. Intell. 40(1), 119–132 (2018)
T.N. Tan, G.D. Sullivan, K.D. Baker, Linear algorithms for object pose estimation, in BMVC92 (Springer, London, 1992), pp. 600–609
P.D. Hanlon, P.S. Maybeck, Multiple-model adaptive estimation using a residual correlation Kalman filter bank. IEEE Trans. Aerosp. Electron. Syst. 36(2), 393–406 (2000)
A.H. Mohamed, K.P. Schwarz, Adaptive Kalman filtering for INS/GPS. J. Geod. 73(4), 193–203 (1999)
D.J. Jwo, S.C. Chang, Particle swarm optimization for GPS navigation Kalman filter adaptation. Aircr. Eng. Aerosp. Technol. 81(4), 343–352 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Assa, A., Janabi-Sharifi, F. (2019). Adaptive 3D Object Pose Estimation Through Particle Swarm Optimization. In: MartÃnez-GarcÃa, A., Bhattacharya, I., Otani, Y., Tutsch, R. (eds) Progress in Optomechatronic Technologies . Springer Proceedings in Physics, vol 233. Springer, Singapore. https://doi.org/10.1007/978-981-32-9632-9_17
Download citation
DOI: https://doi.org/10.1007/978-981-32-9632-9_17
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-32-9631-2
Online ISBN: 978-981-32-9632-9
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)