Papers
2
Total Citations
12
H-Index
2
About
Xiaoning Shen is a leading researcher in multi-robot systems and intelligent optimization, with a primary focus on advancing cooperative robotics through multi-objective decision-making. Shen’s foundational work addresses the inherent complexity of coordinating multiple mobile robots, establishing that task allocation is fundamentally a multi-objective optimization problem. In their most cited paper (2010, 7 citations), Shen developed a general multi-objective task allocation model and a novel genetic algorithm to generate optimal, balanced solutions for robot teams—a critical contribution for real-world applications like warehouse logistics and search-and-rescue. Earlier, Shen pioneered a multi-objective evolutionary programming algorithm (2006, 5 citations) that introduced dual elitism mechanisms, bypassing traditional fitness assignment to solve path planning with three simultaneous objectives. This work demonstrated how heuristic-random hybrid approaches could efficiently navigate trade-offs between path length, safety, and energy. Though citation counts reflect a focused, early-career impact, Shen’s contributions are foundational in the niche of multi-objective robotics, providing frameworks still used by researchers tackling complex coordination problems. Their work remains essential reading for engineers designing autonomous multi-robot systems.
Research Focus
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Top Papers
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