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Traversability Assessment and Reachability Analysis for Unmanned Ground Vehicles through Image Segmentation
Conference proceeding

Traversability Assessment and Reachability Analysis for Unmanned Ground Vehicles through Image Segmentation

Philip Bailey, Andrew Clevenger and Hakki Erhan Sevil
Conference Proceedings: 2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 10092223
IEEE Applied Imagery Pattern Recognition (AIPR 2022) (DC, USA, 10/11/2022–10/13/2022)
04/10/2023
Web of Science ID: WOS:000991969300025

Abstract

A major hurdle for unmanned vehicles is to autonomously navigate in an unstructured environment with different types of terrain traversability. Autonomous navigation requires several tasks, including generating a map from raw data, potentially combining data coming from different sources, interpreting the data to understand traversability, planning a suitable route to the goal, and executing that route. In this study, our objective is to provide a segmentation based traversability assessment and reachability analysis of the environment scenes that would enable more sophisticated decision making with respect to operational maneuvers.

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