  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.
