Papers
1
Total Citations
23
H-Index
1
About
Yicong Jin is a robotics researcher whose work centers on path planning and energy optimization for unconventional mobile platforms, with a particular focus on spherical robots. His most-cited paper, "Improved A* Algorithm for Path Planning of Spherical Robot Considering Energy Consumption" (2023, 23 citations), addresses a critical gap in the field: while existing path planning algorithms for spherical robots prioritize shortest-distance routes, Jin’s innovation integrates energy consumption as a key optimization parameter. This is especially significant given spherical robots’ unique ability to traverse complex terrains—such as swamps, grasslands, and deserts—where energy efficiency directly impacts mission endurance and feasibility. By modifying the classic A* algorithm to account for energy costs, Jin has enhanced the practical deployability of these robots in real-world, resource-constrained environments. His work bridges theoretical algorithm design with applied robotics, offering a more holistic approach to autonomous navigation. Though early in his career, Jin’s contributions are already recognized for addressing a practical limitation in spherical robotics, positioning him as a promising researcher in energy-aware autonomous systems and field robotics.
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Top Papers
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