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20232026
most citedCAHSOR: Competence-Aware High-Speed Off-Road Ground Navigation in SE(3)

16 citations · 20 across the 14 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

Social-LLaVA: Enhancing Robot Navigation through Human-Language Reasoning in Social Spaces

Amirreza Payandeh, Daeun Song, Mohammad Nazeri +6

Most existing social robot navigation techniques either leverage hand-crafted rules or human demonstrations to connect robot perception to socially compliant actions. However, ther…

cs.RO2024

M2P2: A Multi-Modal Passive Perception Dataset for Off-Road Mobility in Extreme Low-Light Conditions

Aniket Datar, Anuj Pokhrel, Mohammad Nazeri +8

Long-duration, off-road, autonomous missions require robots to continuously perceive their surroundings regardless of the ambient lighting conditions. Most existing autonomy system…

cs.RO2024

Traverse the Non-Traversable: Estimating Traversability for Wheeled Mobility on Vertically Challenging Terrain

Chenhui Pan, Aniket Datar, Anuj Pokhrel +3

Most traversability estimation techniques divide off-road terrain into traversable (e.g., pavement, gravel, and grass) and non-traversable (e.g., boulders, vegetation, and ditches)…

cs.RO2024

VertiCoder: Self-Supervised Kinodynamic Representation Learning on Vertically Challenging Terrain

Mohammad Nazeri, Aniket Datar, Anuj Pokhrel +3

We present VertiCoder, a self-supervised representation learning approach for robot mobility on vertically challenging terrain. Using the same pre-training process, VertiCoder can…

cs.RO2024

Terrain-Attentive Learning for Efficient 6-DoF Kinodynamic Modeling on Vertically Challenging Terrain

Aniket Datar, Chenhui Pan, Mohammad Nazeri +2

Wheeled robots have recently demonstrated superior mechanical capability to traverse vertically challenging terrain (e.g., extremely rugged boulders comparable in size to the vehic…

cs.RO2024★ 2 cited

VANP: Learning Where to See for Navigation with Self-Supervised Vision-Action Pre-Training

Mohammad Nazeri, Junzhe Wang, Amirreza Payandeh +1

Humans excel at efficiently navigating through crowds without collision by focusing on specific visual regions relevant to navigation. However, most robotic visual navigation metho…

cs.RO2024★ 16 cited

CAHSOR: Competence-Aware High-Speed Off-Road Ground Navigation in SE(3)

Anuj Pokhrel, Aniket Datar, Mohammad Nazeri +1

While the workspace of traditional ground vehicles is usually assumed to be in a 2D plane, i.e., SE(2), such an assumption may not hold when they drive at high speeds on unstructur…