Efficient Occlusion-Aware Navigation for Air-Ground Robot in Dynamic Environments via State Space Model
- OMEGA (Submitted to RA-L'24): The First AGR-Tailored Dynamic Navigation System.
- AGRNav (ICRA'24): The First AGR-Tailored Occlusion-Aware Navigation System.
- [03/07/2024]: OMEGA's simulation logs are available for download:
- [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!
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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- SemanticKITTI
Many thanks to these excellent open source projects: