In this chapter, we investigate a UAV-enabled wireless power transfer (WPT) network, where an unmanned aerial vehicle (UAV) flies at a constant altitude to wirelessly supply energy to multiple ground nodes arranged in a linear topology. Our goal is to maximize the minimum received energy among all ground nodes by optimizing the UAV one-dimensional (1D) trajectory, subject to the maximum UAV speed constraint. Unlike previous studies that only provided heuristic or locally optimal solutions, this work is the first to propose a globally optimal 1D trajectory solution for the considered problem. Specifically, we first demonstrate that for any given speed-constrained UAV trajectory, an equivalent combination of a maximum-speed trajectory and a speed-free trajectory can be constructed to achieve the same energy reception for all ground nodes. We then reformulate the original speed-constrained trajectory optimization problem into an equivalent speed-free problem, which is subsequently solved using the Lagrange dual method. The resulting optimal UAV trajectory follows a successive hover-and-fly (SHF) structure, where the UAV hovers at a finite set of locations for optimized durations and flies between them at maximum speed. Building on the derived optimal trajectory structure, we also present a low-complexity trajectory design. This approach first reformulates the problem as an equivalent non-convex optimization with only UAV hovering locations and durations as optimization variables. Then, the successive convex approximation (SCA) technique is applied to iteratively refine the trajectory, ensuring convergence to a suboptimal solution with significantly lower computational complexity, regardless of the geographical network size. Numerical results validate the performance of the proposed low-complexity trajectory design, demonstrating that it achieves the same energy efficiency as the optimal solution. Moreover, both the optimal and low-complexity designs outperform existing benchmark algorithms across different scenarios, highlighting their effectiveness in UAV-enabled WPT networks.