Work

Path Planning and Optimization Algorithm for Mobile Assisted Localization Robots

Year: 2025

Type: conference-paper

Abstract: In many sensor network applications, localization is a crucial technology because the lack of sensor location information can lead to operational failures. Using mobile-assisted localization robots equipped with GPS receivers to assist sensor localization is a cost-effective approach. This study deployed beacon points using a triangular layout strategy and generated complete coverage paths using the SCAN algorithm. The study proposes the Obstacle Patterned Locational Pathing (OPLAP) to ensure the mobile-assisted localization robot traverses all beacon points precisely once. Experimental results demonstrate that OPLAP excels in full coverage and enhanced localization accuracy.

Source: Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence (DEAI)

DOI: 10.1145/3745238.3745242

Authors: Delin Luo, Tianxiang Huang, Lin Lin, Xinxin Chen, Rong-Guei Tsai

Institutions: Putian University, Guangdong University of Science and Technology

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

OpenAlex ID: W4412790065

FWCI:

Cites: 13

Cited by:

Related to: 10