Papers
4
Total Citations
28
H-Index
3
About
Shiyuan Wang is a robotics researcher whose work focuses on advancing autonomous navigation and path planning for wheeled robots in complex, three-dimensional environments. Wang’s key contributions lie in developing algorithms that move beyond traditional 2D flat-terrain assumptions, addressing the computational and informational challenges of real-world terrain. Their most cited work, the LSPP algorithm (10 citations), innovatively uses line segment features instead of point features for obstacle evaluation, reducing computational burden while preserving critical environmental information. Wang further extended this to 3D with a hierarchical navigation system that leverages statistical features of point clouds (10 citations), enabling efficient mapping and path planning in complex terrain. Another notable contribution fuses an improved A* algorithm with the Timed Elastic Band (TEB) approach (6 citations), smoothing path curves and eliminating jumpy command outputs for more stable robot motion. Wang’s research is characterized by a practical, optimization-based approach, as seen in their recent work on hybrid maps for complex terrain (2 citations). With a growing citation record and a focus on bridging the gap between theoretical path planning and real-world robotic deployment, Shiyuan Wang is establishing themselves as a thoughtful contributor to the field of autonomous navigation.
Research Focus
Key Achievements
Top Papers
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