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10.1109/IROS.2015.7353514guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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Scene understanding for a high-mobility walking robot

Published: 28 September 2015 Publication History

Abstract

High-mobility walking robots offer unique capabilities in complex off-road environments where wheeled vehicles are not able to travel. However, these environments can also pose significant autonomous navigation challenges. Key steps in planning a safe path for the robot autonomously include estimating the height of the support ground surface - which is often occluded by vegetation - and classifying the terrain and obstacles above the ground surface. This paper describes the development and experimental evaluation of a terrain classification and ground surface height estimation system to support autonomous navigation for a high-mobility walking robot. We provide experimental evaluation on an extensive, manually-labeled dataset collected from geographically diverse sites over a 28-month period.

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Cited By

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  • (2018)Incremental Learning of Traversability Cost for Aerial Reconnaissance Support to Ground UnitsModelling and Simulation for Autonomous Systems10.1007/978-3-030-14984-0_30(412-421)Online publication date: 17-Oct-2018

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          cover image Guide Proceedings
          2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
          Sep 2015
          6501 pages

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          IEEE Press

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          Published: 28 September 2015

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          • (2018)Incremental Learning of Traversability Cost for Aerial Reconnaissance Support to Ground UnitsModelling and Simulation for Autonomous Systems10.1007/978-3-030-14984-0_30(412-421)Online publication date: 17-Oct-2018

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