A three-dimensional point cloud registration based on entropy and particle swarm optimization-Reference-Cited by-同舟云学术

A three-dimensional point cloud registration based on entropy and particle swarm optimization

Published:2018-12 Issue:12 Volume:10 Page:168781401881433
ISSN:1687-8140
Container-title:Advances in Mechanical Engineering
language:en
Short-container-title:Advances in Mechanical Engineering

Author:

Zhan Xu¹²,Cai Yong¹,He Ping²³⁴^ORCID

Affiliation:

1. School of Information Engineering, Southwest University of Science and Technology, Mianyang, People’s Republic of China

2. Cooperative Control & System Optimization Laboratory, Department of Automation, School of Automation and Information Engineering, Sichuan University of Science & Engineering, Yibin, People’s Republic of China

3. Smart Construction Laboratory, The Hong Kong Polytechnic University, Kowloon, Hong Kong

4. Emerging Technologies Institute, Faculty of Engineering, The University of Hong Kong, Hong Kong

Abstract

A three-dimensional (3D) point cloud registration based on entropy and particle swarm algorithm (EPSA) is proposed in the paper. The algorithm can effectively suppress noise and improve registration accuracy. Firstly, in order to find the k-nearest neighbor of point, the relationship of points is established by k-d tree. The noise is suppressed by the mean of neighbor points. Secondly, the gravity center of two point clouds is calculated to find the translation matrix T. Thirdly, the rotation matrix R is gotten through particle swarm optimization (PSO). While performing the PSO, the entropy information is selected as the fitness function. Lastly, the experiment results are presented. They demonstrate that the algorithm is valuable and robust. It can effectively improve the accuracy of rigid registration.

Funder

Open Foundation of Artificial Intelligence Key Laboratory of Sichuan Province

Research Foundation of Department of Education of Sichuan Province

National Natural Science Foundation of China

Open Foundation of Enterprise Informatization and Internet of Things Key Laboratory of Sichuan Province

Open Foundation of Sichuan Provincial Key Lab of Process Equipment and Control

Publisher

SAGE Publications

Subject

Mechanical Engineering

Link

http://journals.sagepub.com/doi/pdf/10.1177/1687814018814330

Reference37 articles.

1. Solenoid model for visualizing magnetic flux leakage testing of complex defects

2. Target State and Markovian Jump Ionospheric Height Bias Estimation for OTHR Tracking Systems

3. Consensus seeking in heterogeneous second-order multi-agent systems with switching topologies and random link failures

4. Short-Term Solar Power Forecasting Based on Weighted Gaussian Process Regression

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The SVD-enhanced bees algorithm, a novel procedure for point cloud registration;Swarm and Evolutionary Computation;2024-07

2. Grey Wolf Optimizer with Behavior Considerations and Dimensional Learning in Three-Dimensional Tooth Model Reconstruction;Bioengineering;2024-03-05

3. Coarse–Fine Registration of Point Cloud Based on New Improved Whale Optimization Algorithm and Iterative Closest Point Algorithm;Symmetry;2023-11-29

4. 3D point cloud global denoising algorithm based on different noise characteristics;Measurement Science and Technology;2023-10-26

5. A Globally Optimal Multi-Constrained Point Cloud Registration Algorithm;2023 International Conference on Advances in Electrical Engineering and Computer Applications (AEECA);2023-08-18