This paper studies the age of information (AoI) minimization problem in an unmanned aerial vehicle (UAV)-assisted wireless powered communication network. Multiple time-constrained UAVs fly to positions within the transmission coverages of the sensor nodes (SNs) to charge them via wireless power transfer (WPT) in the downlink, and collect data from the SNs in the uplink when enough energy have been harvested. Given the dense deployment of SNs within the network, the transmission coverages of different SNs might overlap with each other. We are thus inspired to select some overlapped areas as hovering points (HPs), at which the UAVs conduct WPT and data collection with multiple SNs simultaneously. Accordingly, the HP selection, the wireless resource allocation and the trajectory planning for each UAV should be jointly considered in the AoI minimization problem. Since the optimization problem is nonconvex and thus difficult to be solved, a heuristic three-step algorithm is proposed. Firstly, a joint graph theory and kernel K-means algorithm is proposed to determine the number and positions of the HPs, and put them into different clusters, where each group of HPs is visited by a single UAV. Secondly, convex optimization methods are utilized to solve the wireless resource allocation subproblem. Finally, a time-constrained trajectory planning algorithm is proposed. Simulation results demonstrate that the introduced approach outperforms the traditional methods through effective utilization of overlapped areas.