Jian Wen
Papers
11
Total Citations
297
H-Index
8
About
Jian Wen is a robotics researcher whose work sits at the intersection of autonomous navigation, simultaneous localization and mapping (SLAM), and motion planning for mobile robots. His research has made significant contributions to enabling robots to operate intelligently in complex, unknown environments — both as individual agents and as coordinated multi-robot systems. Among his most influential contributions is a laser-based autonomous exploration framework using polygon map construction and graph-based SLAM with directional endpoint features (2018, 71 citations), which established a robust foundation for indoor robot autonomy. Building on this, his CURE framework (2023, 48 citations) introduced dynamic Voronoi diagrams to coordinate multi-robot exploration efficiently. In motion planning, Wen developed the E³MoP framework (2021, 46 citations), a three-layer hierarchical planner for large-scale complex environments, and a goal-biased bidirectional RRT algorithm with curve-smoothing (2019, 44 citations) that improved path quality and search efficiency. Wen also demonstrated a commitment to rigorous scientific evaluation through MRPB 1.0 (2021, 32 citations), a unified benchmark for assessing mobile robot local planners — a resource of lasting practical value to the research community. Collectively, his work has accumulated over 290 citations, reflecting his growing influence in the autonomous robotics field.
Research Focus
Key Achievements
Top Papers
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- 4Goal-biased Bidirectional RRT based on Curve-smoothing44 citations · 2019
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- 9A Local Planning Method Based on Graph Optimization Framework4 citations · 2021
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