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From the 1 of 11 linked papers with an AI index.

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20242026
most citedBEV-Patch-PF: Particle Filtering with BEV-Aerial Feature Matching for Off-Road Geo-Localization

1 citations · 1 across the 4 of their papers we have counts for

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cs.RO2026

Adapting Generalist Vehicle Models for High-Speed MPC Across Terrains

Rwik Rana, Jesse Quattrociocchi, Christian Ellis +3

The paper introduces OptCar, a method for adapting a generalist forward kinodynamic model to a specific vehicle using minimal real-world data and synthetic rollouts, improving high…

cs.RO20261 cited

BEV-Patch-PF: Particle Filtering with BEV-Aerial Feature Matching for Off-Road Geo-Localization

Dongmyeong Lee, Jesse Quattrociocchi, Christian Ellis +5

We propose BEV-Patch-PF, a GPS-free sequential geo-localization system that integrates a particle filter with learned bird's-eye-view (BEV) and aerial feature maps. From onboard RG…

cs.RO2026

OVerSeeC: Open-Vocabulary Costmap Generation from Satellite Images and Natural Language

Rwik Rana, Jesse Quattrociocchi, Dongmyeong Lee +5

Aerial imagery provides essential global context for autonomous navigation, enabling route planning at scales inaccessible to onboard sensing. We address the problem of generating…

cs.RO2025

COMPASS: Cross-embodiment Mobility Policy via Residual RL and Skill Synthesis

Wei Liu, Huihua Zhao, Chenran Li +4

As robots are increasingly deployed in diverse application domains, enabling robust mobility across different embodiments has become a critical challenge. Classical mobility stacks…

cs.RO2025

X-MOBILITY: End-To-End Generalizable Navigation via World Modeling

Wei Liu, Huihua Zhao, Chenran Li +5

General-purpose navigation in challenging environments remains a significant problem in robotics, with current state-of-the-art approaches facing myriad limitations. Classical appr…

cs.RO2025

cuVSLAM: CUDA accelerated visual odometry and mapping

Alexander Korovko, Dmitry Slepichev, Alexander Efitorov +5

Accurate and robust pose estimation is a key requirement for any autonomous robot. We present cuVSLAM, a state-of-the-art solution for visual simultaneous localization and mapping,…