<p>This study presents a groundbreaking investigation into the optimization of trajectories for aerial manipulators engaged in object grasping and control along predefined paths. We introduce an innovative multi-body dynamic model inspired by birds of prey, which integrates an aerial vehicle, an articulated arm, and a gripper featuring an additional degree of freedom, enhancing operational flexibility. The incorporation of target mass and this new degree of freedom markedly influences system dynamics, leading to significant variations in the center of mass and overall state variables. Using a genetic algorithm, we generate optimal trajectories for the grasping phase, revealing that a two-degree-of-freedom claw substantially enhances the vehicle’s capability to grasp objects across diverse positions and orientations. This advancement enables versatile aerial manipulation, allowing for precise adjustments in position, orientation, and velocity. Focusing specifically on aerial manipulation during forward flight, the study emphasizes the simultaneous generation of trajectories and manipulation while sustaining forward motion with minimal control efforts under various system constraints. Simulations illustrate a remarkable 10% reduction in control effort when utilizing optimized trajectories compared to traditional methods, resulting in smoother flight paths and improved energy efficiency. Moreover, the aerial manipulator successfully grasps targets at a velocity of 0.1&#xa0;m/s at the grasping point, demonstrating stable and reliable performance across multiple test scenarios. These findings underscore the effectiveness of our genetic algorithm-based optimization in enhancing grasping accuracy and system efficiency, presenting a robust solution for advanced aerial manipulation tasks.</p>