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<div align="center"> <h1>🤖 OMEGA</h1> <h2>Efficient Occlusion-Aware Navigation for Air-Ground Robot in Dynamic Environments via State Space Model</h2> <br> <a href='https://arxiv.org/abs/2408.10618'><img src='https://img.shields.io/badge/arXiv-OMEGA-green' alt='arxiv'></a> <a href='https://jmwang0117.github.io/OMEGA/'><img src='https://img.shields.io/badge/Project_Page-OMEGA-green' alt='Project Page'></a> </div>

🤗 AGR-Family Works

📢 News

<div align="center">
Simulation ResultsExperiment Log
OMEGAlink
AGRNavlink
TABVlink
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OccMamba ResultsExperiment Log
OccMamba on the SemanticKITTI hidden official test datasetlink
OccMamba test loglink
OccMamba evaluation loglink
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📜 Introduction

OMEGA emerges as the pioneering navigation system tailored for AGRs in dynamic settings, with a focus on ensuring occlusion-free mapping and pathfinding. It incorporates OccMamba, a module designed to process point clouds and perpetually update local maps, thereby preemptively identifying obstacles within occluded areas. Complementing this, AGR-Planner utilizes up-to-date maps to facilitate efficient and effective route planning, seamlessly navigating through dynamic environments.

<p align="center"> <img src="misc/head.png" width = 60% height = 60%/> </p> <br> 
@article{wang2024omega,
  title={OMEGA: Efficient Occlusion-Aware Navigation for Air-Ground Robot in Dynamic Environments via State Space Model},
  author={Wang, Junming and Huang, Dong and Guan, Xiuxian and Sun, Zekai and Shen, Tianxiang and Liu, Fangming and Cui, Heming},
  journal={arXiv preprint arXiv:2408.10618},
  year={2024}
}
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🛠️ Installation

TODO

💽 Dataset

🏆 Acknowledgement

Many thanks to these excellent open source projects: