PTS-Map: Probabilistic Terrain State Map for Uncertainty-Aware Traversability Mapping in Unstructured Environments

Traversability mapping for autonomous navigation in unstructured environments has been widely investigated for decades. However, it remains challenging due to the uncertainty in geometry perception and the simplified representation of traversability maps that fail to capture detailed structures of environments. We propose PTS-Map, a 2.5D probabilistic terrain state map to address these issues. PTS-Map sequentially updates the ground surface state and above-ground elevation state, explicitly distinguishing the geometric features of ground and obstacles. During state updates, we introduce a novel ground uncertainty estimation to mitigate the effects of unreliable feature measurements. By effectively designing the terrain states and addressing the geometric feature uncertainty, PTS-Map constructs a temporally consistent traversability map that provides precise ground conditions and vertical features relevant to navigation. Experiments are conducted in various large-scale unstructured environments with distinct characteristics. PTS-Map outperforms other state-of-the-art methods in success rate and efficiency by constructing a precise traversability map.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-12-18
DOI
https://doi.org/10.1109/lra.2024.3519859
Citations
1
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
0.33
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article

PTS-Map: Probabilistic Terrain State Map for Uncertainty-Aware Traversability Mapping in Unstructured Environments

Dong-Wook Kim, E In Son, Seung‐Woo Seo, Ji-Hoon Hwang et al.
1 citations
IEEE Robotics and Automation Letters
Robotics and Automated Systems
0.33
article

PTS-Map: Probabilistic Terrain State Map for Uncertainty-Aware Traversability Mapping in Unstructured Environments

Dong-Wook Kim, E In Son, Seung‐Woo Seo, Ji-Hoon Hwang, Chan Kim
article en
1 citations

Abstract

Traversability mapping for autonomous navigation in unstructured environments has been widely investigated for decades. However, it remains challenging due to the uncertainty in geometry perception and the simplified representation of traversability maps that fail to capture detailed structures of environments. We propose PTS-Map, a 2.5D probabilistic terrain state map to address these issues. PTS-Map sequentially updates the ground surface state and above-ground elevation state, explicitly distinguishing the geometric features of ground and obstacles. During state updates, we introduce a novel ground uncertainty estimation to mitigate the effects of unreliable feature measurements. By effectively designing the terrain states and addressing the geometric feature uncertainty, PTS-Map constructs a temporally consistent traversability map that provides precise ground conditions and vertical features relevant to navigation. Experiments are conducted in various large-scale unstructured environments with distinct characteristics. PTS-Map outperforms other state-of-the-art methods in success rate and efficiency by constructing a precise traversability map.

IEEE Robotics and Automation LettersVol. 10(2)
Seoul National University (KR)
Climate action
Openalex Percentile: Top 38%
Robotics and Automated Systems
0.33
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PTS-Map: Probabilistic Terrain State Map for Uncertainty-Aware Traversability Mapping in Unstructured Environments — Dong-Wook Kim, E In Son, et al. · IEEE Robotics and Automation Letters (2024) | TGRS Research Map | TGRS