Quan-Ke Pan
Papers
9
Total Citations
177
H-Index
7
About
Quan-Ke Pan is a leading researcher in intelligent robotics and multi-agent systems, with a primary focus on task allocation and scheduling for agricultural robots. His work directly addresses the optimization challenges of smart farming, developing novel algorithms to coordinate fleets of weeding robots, pollination drones, and picking robots across complex orchard and farm environments. Pan’s major contributions include pioneering the application of discrete artificial bee colony algorithms and multi-objective teaching-learning-based optimizers to agricultural robot task assignment, significantly improving both cost-efficiency and operational speed in smart farms. His most cited paper, "Multi-Objective Multi-Picking-Robot Task Allocation" (2023), has garnered 51 citations, while his 2024 work on multi-weeding robot assignment has 44 citations, reflecting strong and growing impact. Beyond agriculture, Pan has advanced formation control for heterogeneous multi-agent systems and nonholonomic mobile robots, integrating event-triggered mechanisms and reinforcement learning. His recent 2025 studies on knowledge-based evolutionary algorithms for multi-orchard scenarios demonstrate his continued innovation. Pan’s research is essential for students and engineers working at the intersection of operations research, swarm robotics, and precision agriculture.
Research Focus
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Top Papers
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