Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Pfeifer, Tim"'
Consistent motion estimation is fundamental for all mobile autonomous systems. While this sounds like an easy task, often, it is not the case because of changing environmental conditions affecting odometry obtained from vision, Lidar, or the wheels t
Externí odkaz:
http://arxiv.org/abs/2204.04149
Publikováno v:
In Transportation Research Part F: Psychology and Behaviour July 2024 104:88-108
Gaussian mixtures are a powerful and widely used tool to model non-Gaussian estimation problems. They are able to describe measurement errors that follow arbitrary distributions and can represent ambiguity in assignment tasks like point set registrat
Externí odkaz:
http://arxiv.org/abs/2103.02472
Accurate and reliable tracking of multiple moving objects in 3D space is an essential component of urban scene understanding. This is a challenging task because it requires the assignment of detections in the current frame to the predicted objects fr
Externí odkaz:
http://arxiv.org/abs/2008.05309
The recently proposed factor graph optimization (FGO) is adopted to integrate GNSS/INS attracted lots of attention and improved the performance over the existing EKF-based GNSS/INS integrations. However, a comprehensive comparison of those two GNSS/I
Externí odkaz:
http://arxiv.org/abs/2004.10572
Autor:
Pfeifer, Tim, Protzel, Peter
GNSS localization is an important part of today's autonomous systems, although it suffers from non-Gaussian errors caused by non-line-of-sight effects. Recent methods are able to mitigate these effects by including the corresponding distributions in
Externí odkaz:
http://arxiv.org/abs/1904.13279
Autor:
Pfeifer, Tim, Protzel, Peter
Publikováno v:
2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 3151-3157
Non-Gaussian and multimodal distributions are an important part of many recent robust sensor fusion algorithms. In difference to robust cost functions, they are probabilistically founded and have good convergence properties. Since their robustness de
Externí odkaz:
http://arxiv.org/abs/1811.04748
Autor:
CONNOLLY, JIM
Publikováno v:
National Underwriter / Life & Health Financial Services. 1/25/99, Vol. 103 Issue 4, p1. 2p.
Autor:
Pfeifer, Tim
This thesis offers a probabilistic solution to robust estimation using a novel adaptive estimator. Reliable state estimation is a mandatory prerequisite for autonomous systems interacting with the real world. The presence of outliers challenges the G
Publikováno v:
Fund Action. 4/16/2012, p43-43. 1p.