5 citations · 7 across the 4 of their papers we have counts for
4 papers
Multimodal Fused Learning for Solving the Generalized Traveling Salesman Problem in Robotic Task Planning
Jiaqi Cheng, Mingfeng Fan, Xuefeng Zhang +4
Effective and efficient task planning is essential for mobile robots, especially in applications like warehouse retrieval and environmental monitoring. These tasks often involve se…
DL-DRL: A double-level deep reinforcement learning approach for large-scale task scheduling of multi-UAV
Xiao Mao, Zhiguang Cao, Mingfeng Fan +2
Exploiting unmanned aerial vehicles (UAVs) to execute tasks is gaining growing popularity recently. To solve the underlying task scheduling problem, the deep reinforcement learning…
An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problem
Bingjie Li, Guohua Wu, Yongming He +2
Vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem, and many models and algorithms have been proposed to solve the VRP and its variants. Althoug…
An Autonomous Path Planning Method for Unmanned Aerial Vehicle based on A Tangent Intersection and Target Guidance Strategy
Huan Liu, Xiamiao Li, Mingfeng Fan +3
Unmanned aerial vehicle (UAV) path planning enables UAVs to avoid obstacles and reach the target efficiently. To generate high-quality paths without obstacle collision for UAVs, th…