Radar-Based Pothole Detection and Optimal Path Evaluation Using Machine Learning

Le résumé fourni par la source

In this paper, we describe a simulation-based framework for detecting potholes using radar in addition to assessing optimal routes over roads of varying surface materials using machine learning. This framework creates B-scan radar signals that simulate the ground plane with different terrains and materials. After extracting the signal features, we train supervised learning models to classify the potholes. In addition to this, we apply a feature-based scoring approach to score terrain segments to filter and obtain the desirable driving route.

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