Despite the growing interest for autonomous environmental monitoring, effective SLAM realization in native habitats remains largely unsolved. In this paper, we fill this gap by presenting a novel online graph-based SLAM system for 2D LiDAR sensor in natural environments. By taking advantage of robust weighting scheme, sliding-windowed optimization, fast scan-matcher and parallel computing, our system not only delivers stable performance in cluttered surroudings but also meets real-time constraint. Simulated and experimental results confirm the feasibility and efficiency in the overall design of the proposed system.
@article{arxiv.2101.06615,
title = {Online Robust Sliding-Windowed LiDAR SLAM in Natural Environments},
author = {Quang-Ha Pham and Ngoc-Huy Tran and Thanh-Toan Nguyen and Thien-Phuc Tran},
journal= {arXiv preprint arXiv:2101.06615},
year = {2021}
}
Comments
Add figure 2 for clearer explanation. in 2021 International Symposium on Electrical and Electronics Engineering (ISEE), Ho Chi Minh City, 2021