@inproceedings{5f6fcf08a157467c8750f892d4336f7f,
title = "2D Lidar Data Matching: Using Simulated Annealing on Point-Based Method",
abstract = "The paper proposes a novel, simple but effective method to align 2D LiDAR laser data. The method uses point-based approach with a simulated annealing searching algorithm. Iterative Closest Point (ICP) is a common method used to solve 2D Lidar alignment problem and widely used to solve Simultaneous localization and mapping (SLAM) problem. The local minima problem allows ICP can be applied only in final aligning steps where data are roughly aligned. The proposed method solves this problem by using simulated annealing (SA) searching algorithm to align two data from distance. SA works on point medium on a point-based approach to reduce the searching dimensions and enhance convergence rate. The method has proved its robustness and efficiency in aligning 2D LiDAR laser data.",
keywords = "2D LiDAR laser, 2D scan matching, Point-based method, Simulated annealing",
author = "Linh Tao and Tinh Nguyen and Trung Nguyen and Toshio Ito and Tam Bui",
note = "Funding Information: Ackknowledgement. This work is supported by School of Mechanical Engineering, Hanoi University of Science and Technology under a project named T2020-PC-010. Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 6th IFToMM Asian Mechanisms and Machine Science Conference, Asian MMS 2021 ; Conference date: 15-12-2021 Through 18-12-2021",
year = "2022",
doi = "10.1007/978-3-030-91892-7_90",
language = "English",
isbn = "9783030918910",
series = "Mechanisms and Machine Science",
publisher = "Springer Science and Business Media B.V.",
pages = "944--949",
editor = "Khang, {Nguyen Van} and Hoang, {Nguyen Quang} and Marco Ceccarelli",
booktitle = "Advances in Asian Mechanism and Machine Science - Proceedings of IFToMM Asian MMS 2021",
}