NDLI: Hybrid map-based SLAM using a Velodyne laser scanner

Content Provider	IEEE Xplore Digital Library
Author	Jaebum Choi
Copyright Year	2014
Description	Author affiliation: Inst. of Control Eng., Tech. Univ. Braunschweig, Braunschweig, Germany (Jaebum Choi)
Abstract	The first step of environment perception for autonomous vehicles is to estimate the trajectories of the ego vehicle. Based on this, we can build the map of the environment and decide the behaviours of the vehicle in the future. Since a Global Navigation Satellite System (GNSS) is inaccurate and not available in all situations, the Simultaneous Localization and Mapping (SLAM) technique has been introduced to solve this problem. In this paper, we propose a hybrid map-based SLAM using Rao-Blackwellized particle filters (RBPFs). Especially, it was designed with the Velodyne 3D HDL-64 laser scanner which provides rich and accurate data of spatial information around the vehicle. Therefore, our work comprises not only the RBPFs framework but also some signal preprocessing procedures of the sensor. Unlike prior works, we describe the environment by using a grid map and a feature map together rather than using only one of them. Based on both maps, we have formulated a new proposal distribution which is an important performance factor of the algorithm. This makes the uncertainty of a predicted vehicle position decrease drastically and therefore the robustness and efficiency of the algorithm can also be improved. The presented approach was implemented on our experimental vehicle and evaluated in the complex urban scenarios. The test results prove that our approach works well even in real outdoor environments and outperforms traditional approaches.
Starting Page	3082
Ending Page	3087
File Size	2146456
Page Count	6
File Format	PDF
ISBN	9781479960781
DOI	10.1109/ITSC.2014.6958185
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-08
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicles Simultaneous localization and mapping Proposals Atmospheric measurements Particle measurements Trajectory Estimation
Content Type	Text
Resource Type	Article

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