Data supporting: 'Hybrid Terrain Traversability Analysis in Off-road Environments'

Date published

2022-09-05 10:37

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Cranfield University

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Software

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Citation

Leung, Tiga (2022). Data supporting: 'Hybrid Terrain Traversability Analysis in Off-road Environments'. Cranfield Online Research Data (CORD). Software. https://doi.org/10.17862/cranfield.rd.19668642

Abstract

Citation: Leung THY, Ignatyev D, Zolotas A. (2022) Hybrid terrain traversability analysis in off-road environments. In: 2022 8th International Conference on Automation, Robotics and Applications (ICARA), 18 February - 20 March 2022, Prague, Czech RepublicAbstract: There is a significant growth in autonomy level in off-road ground vehicles. However, unknown off-road environments are often challenging due to their unstructured and rough nature. To find a path that the robot can move smoothly to its destination, it needs to analyse the surrounding terrain. In this paper, we present a hybrid terrain traversability analysis framework. Semantic segmentation is implemented to understand different types of the terrain surrounding the robot; meanwhile geometrical properties of the terrain are assessed with the aid of a probabilistic terrain estimation. The framework represents the traversability analysis on a robot-centric cost map, which is available to the path planners. We evaluated the proposed framework with synchronised sensor data captured while driving the robot in real off-road environments. This thorough terrain traversability analysis will be crucial for autonomous navigation systems in off-road environments.

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Keywords

terrain traversability analysis', 'off-road environments', 'elevation mapping', 'semantic segmentation', 'cost map'

DOI

10.17862/cranfield.rd.19668642

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MIT

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