Research on UAV technology contribution evaluation based on BRB-ER method

This study proposes a model based on a belief rule base (BRB) and an evidence reasoning (ER) algorithm to evaluate the contribution of UAV technology to navigation capabilities. In a changing and uncertain environment, a single navigation technology can no longer meet the needs of high-precision positioning and path planning for modern UAVs. To this end, this model dynamically adjusts the belief of the rule base by changing the benchmark parameter value, and uses multiple technical indicators such as navigation accuracy, sensor performance, and obstacle avoidance to quantitatively evaluate the contribution of each technology. Experimental results show that the model can effectively handle the contribution of each technology in task execution and help decision makers to make reasonable technology deployment and optimization in complex environments. This method provides a quantitative evaluation framework for the multi-field application of UAV technology, which is of great significance, especially in improving the accuracy of navigation technology and task efficiency.

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Publication Details

Published
2025-02-21
DOI
https://doi.org/10.1145/3732945.3732966
Primary Topic
Advanced Decision-Making Techniques
Type
article
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article

Research on UAV technology contribution evaluation based on BRB-ER method

Xingyu Wang, Y.H. Chen, Pei-Shu Fan
Advanced Decision-Making Techniques
article

Research on UAV technology contribution evaluation based on BRB-ER method

Xingyu Wang, Y.H. Chen, Pei-Shu Fan
article en

Abstract

This study proposes a model based on a belief rule base (BRB) and an evidence reasoning (ER) algorithm to evaluate the contribution of UAV technology to navigation capabilities. In a changing and uncertain environment, a single navigation technology can no longer meet the needs of high-precision positioning and path planning for modern UAVs. To this end, this model dynamically adjusts the belief of the rule base by changing the benchmark parameter value, and uses multiple technical indicators such as navigation accuracy, sensor performance, and obstacle avoidance to quantitatively evaluate the contribution of each technology. Experimental results show that the model can effectively handle the contribution of each technology in task execution and help decision makers to make reasonable technology deployment and optimization in complex environments. This method provides a quantitative evaluation framework for the multi-field application of UAV technology, which is of great significance, especially in improving the accuracy of navigation technology and task efficiency.

Openalex Percentile: Top 79%
Advanced Decision-Making Techniques
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Research on UAV technology contribution evaluation based on BRB-ER method — Xingyu Wang, Y.H. Chen, et al. · (2025) | TGRS Research Map | TGRS