SEE-CSOM: sharp-edged and efficient continuous semantic occupancy mapping for mobile robots
Generating an accurate and continuous semantic occupancy map is a key component of autonomous robotics. Most existing continuous semantic occupancy mapping methods neglect the potential differences between voxels, which reconstruct an overinflated map. What is more, these methods have high computati...
Main Authors: | Deng, Yinan, Wang, Meiling, Yang, Yi, Wang, Danwei, Yue, Yufeng |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/172336 |
Similar Items
-
Probabilistic reasoning for unique role recognition based on the fusion of semantic-interaction and spatio-temporal features
by: Yang, Chule, et al.
Published: (2019) -
A hierarchical framework for collaborative probabilistic semantic mapping
by: Yue, Yufeng, et al.
Published: (2021) -
Probabilistic 3D semantic map fusion based on Bayesian rule
by: Yue, Yufeng, et al.
Published: (2021) -
Semantic Knowledge-Based Hierarchical Planning Approach for Multi-Robot Systems
by: Sanghyeon Bae, et al.
Published: (2023-05-01) -
Collaborative semantic understanding and mapping framework for autonomous systems
by: Yue, Yufeng, et al.
Published: (2021)