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[RA-L 2024] OMEGA: Efficient Occlusion-Aware Navigation for Air-Ground Robot in Dynamic Environments via State Space Model

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🤖 OMEGA

Efficient Occlusion-Aware Navigation for Air-Ground Robot in Dynamic Environments via State Space Model


arxiv Project Page

🤗 AGR-Family Works

  • OMEGA (RA-L 2024.12): The First AGR-Tailored Dynamic Navigation System.
  • HE-Nav (RA-L 2024.09): The First AGR-Tailored ESDF-Free Navigation System.
  • AGRNav (ICRA 2024.01): The First AGR-Tailored Occlusion-Aware Navigation System.

📢 News

  • [03/07/2024]: OMEGA's simulation logs are available for download:
Simulation Results Experiment Log
OMEGA link
AGRNav link
TABV link
  • [01/07/2024]: OccMamba's test and evaluation logs are available for download:
OccMamba Results Experiment Log
OccMamba on the SemanticKITTI hidden official test dataset link
OccMamba test log link
OccMamba evaluation log link
  • [28/06/2024]: The pre-trained model can be downloaded at OneDrive
  • [25/06/2024]: We have released the code for OccMamba, a key component of OMEGA!

📜 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.


@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

  • SemanticKITTI

🏆 Acknowledgement

Many thanks to these excellent open source projects:

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