Dynamic Path Planning for QoS Improvement in Multiple Automated Guided Vehicles

This paper studies the trajectory optimization of an automated guided vehicle (AGV) for a smart factory where material handling with high wireless communication quality is required. This design aims to maximize the sum of spectral efficiency under complex continuous-value constraints on movement and combinatorial constraints on cooperative movements. To tackle the NP-hard optimization problem, this paper proposes a hybrid algorithm that combines global and local optimization, where global optimization meets the constraints with relaxation and local optimization considers all constraints on movements. Specifically, the AGVs travel by local path planning based on dynamic window approach (DWA), given the globally optimal trajectory that is solved using dynamic programming (DP). Finally, simulation results provide the high communication quality achieved by the proposed algorithm compared to the benchmark algorithms.