A Joint Data Association Method for Laser-SLAM of Unmanned Delivery Vehicle Based on Heuristic Search Algorithm. (23rd November 2022)

• Record Type: Journal Article
• Authors: Liu, Dan; Feng, Yongkang; Han, Zhifeng; Zou, Bo
• Other Names: Marques Carlos Academic Editor.
• Is Part Of: Journal of sensors. Volume 2022(2022)
• Publication Date: 2022-11-23
• Subjects: Detectors -- Periodicals; 681.205
• DOI: 10.1155/2022/1491079
• Languages: English
• ISSNs: 1687-725X

Abstract

Abstract : In Laser-SLAM system of unmanned delivery vehicle, there are two kinds of association methods applied to solve the data association problem. Compared with the method of independent association for a single measurement and a single feature, the methods of batch association of measurements and features can provide more accurate association results in the state estimation stage of SLAM. In order to obtain a better association solution, a joint data association method based on heuristic search algorithm (HSA-JDA) is proposed to improve the robustness and accuracy of data association. In HSA-JDA, according to the joint maximum likelihood criterion, the data association problem is evolved into a combinatorial optimization problem of how to determine the optimal association set. A heuristic search algorithm that is an optimized artificial fish swarm algorithm by using adaptive step size and adding fish swarm jumping behavior is applied to search the optimal association solution. Experimental results show that HSA-JDA method ensures high association accuracy and then improves the robustness and accuracy of the whole state estimation results of SLAM. It can be used in the Laser-SLAM system based on Kalman filter to provide reliable association results for improving the accuracy of SLAM estimation results for unmanned delivery vehicle.