Cargando…
Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning
Place recognition is critical for both offline mapping and online localization. However, current single-sensor based place recognition still remains challenging in adverse conditions. In this paper, a heterogeneous measurement based framework is proposed for long-term place recognition, which retrie...
Autores principales: | Yin, Huan, Xu, Xuecheng, Wang, Yue, Xiong, Rong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8166203/ https://www.ncbi.nlm.nih.gov/pubmed/34079825 http://dx.doi.org/10.3389/frobt.2021.661199 |
Ejemplares similares
-
Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding
por: Pearson, Martin J., et al.
Publicado: (2021) -
Lost in the Woods? Place Recognition for Navigation in Difficult Forest Environments
por: Garforth, James, et al.
Publicado: (2020) -
Deep Learned Quantization-Based Codec for 3D Airborne LiDAR Point Cloud Images
por: Tamilmathi, A. Christoper, et al.
Publicado: (2021) -
On the precision of 6 DoF IMU-LiDAR based localization in GNSS-denied scenarios
por: Frosi, Matteo, et al.
Publicado: (2023) -
Cooperative and Competitive Reinforcement and Imitation Learning for a Mixture of Heterogeneous Learning Modules
por: Uchibe, Eiji
Publicado: (2018)