Localization in highly dynamic environments using dual-timescale NDT-MCL
By Rafael Valencia, J. Saarinen, Henrik Andreasson, Joan Vallvé, J. Andrade-Cetto, Achim J. Lilienthal. 2014
60 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Civil and Structural Engineering, Electrical and Electronic Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Kazuya Takeda
- Ekim Yurtsever
- Alexander Carballo
- Jacob Lambert
- Yoshiki Ninomiya
- Naoki Akai
- Luis Yoichi Morales Saiki
- Yuki Yoshihara
In Electrical and Electronic Engineering
Citations in the corpus
- A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2019, methodology): “An NDT-based Monte Carlo Localization (MCL) method that utilizes an offline static map and a constantly updated shortterm map was developed by [120].”
- Robust localization using 3D NDT scan matching with experimentally determined uncertainty and road marker matching (2017, methodology): “They also proposed an extended method that uses dual time-scale ND maps to improve the robustness to environmental change [19].”
- Autonomous driving based on accurate localization using multilayer LiDAR and dead reckoning (2017, methodology): “NDT-based MCL methods that combine NDT-based localization and dead reckoning have been proposed previously [14], [15].”