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.
翻译：尽管人们对自主环境监测的兴趣日益浓厚,但在本地生境中有效实现SLM的工作基本上仍未解决。 在本文件中,我们通过为自然环境中的2D LiDAR传感器推出一个新的基于图形的SLM在线系统来填补这一空白。 通过利用稳健的权重计划、滑动式窗口优化、快速扫描仪和平行计算,我们的系统不仅在杂乱的杂交中实现了稳定的性能,而且还遇到了实时制约。 模拟和实验结果证实了拟议系统总体设计的可行性和效率。
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