返回
An Enhanced Food Digestion Algorithm for Mobile Sensor Localization
DOI:10.3390/s23177508.png)
摘要
En 中文
Mobile sensors can extend the range of monitoring and overcome static sensors' limitations and are increasingly used in real-life applications. Since there can be significant errors in mobile sensor localization using the Monte Carlo Localization (MCL), this paper improves the food digestion algorithm (FDA). This paper applies the improved algorithm to the mobile sensor localization problem to reduce localization errors and improve localization accuracy. Firstly, this paper proposes three inter-group communication strategies to speed up the convergence of the algorithm based on the topology that exists between groups. Finally, the improved algorithm is applied to the mobile sensor localization problem, reducing the localization error and achieving good localization results.
Keyword:
food digestion algorithm
parallel strategy
compact strategy
mobile sensors
Monte Carlo Localization
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration结合元启发式Salp群算法和确定性协调多机器人探索未知空间
SENSORS
IF3.5
Photosensitization of ZnO rod electrodes with AgInS2nanoparticles and ZnS-AgInS2solid solution nanoparticles for solar cell applications
RSC Adv.
IF0

