Evaluation of Autonomous Navigation Robustness Based on Analytic Hierarchy Process
ID：114
Submission ID：11 View Protection：ATTENDEE
Updated Time：2024-10-23 10:00:24 Hits：25
Poster Presentation
Start Time：Pending （Asia/Shanghai）
Duration：Pending
Session：[No Session] » [No Session Block]
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Abstract
The working environment of autonomous navigation systems is complex and varied, with a wide range of tasks to be executed. Therefore, both academia and industry have put forward high requirements for the robustness of autonomous navigation systems, so accurate and reasonable performance evaluation of the robustness of autonomous navigation systems is very important. However, there is currently no standard evaluation model to measure the robustness performance of autonomous navigation systems. Based on this issue, this article proposes four basic indicators through in-depth research and analysis of autonomous navigation systems: interference loss, norm loss function, path smoothness, and coefficient of determination. The basic indicator values are calculated by processing data such as path trajectory coordinate points and autonomous navigation time. On this basis, a robust performance evaluation model for autonomous navigation based on Analytic Hierarchy Process (AHP) was proposed. Each indicator was weighted to obtain the robust performance evaluation results, and the rationality of the indicator weights was verified through consistency testing, achieving quantitative evaluation of the robust performance of autonomous navigation systems. Through experiments, it has been shown that our method can reasonably and effectively evaluate the robustness performance of autonomous navigation systems, which is of great significance in the improvement of autonomous navigation systems and system performance enhancement.
Keywords
Autonomous navigation system,Analytic hierarchy process,robustness, Performance evaluation
Speaker
hongtaoyin
Prof Harbin Institute of TechnologySubmission Author
All comments
15th August 2024 31st August 2024- Manuscript Submission
15th September 2024 - Acceptance Notification
1st October 2024 - Camera Ready Submission
1st October 2024 – Early Bird Registration
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