Intelligent Unmanned Aerial Vehicle System for Automated Red Pine Cone Harvesting in Dense Forests

This paper describes an intelligent unmanned aerial vehicle (UAV) system that automates red pine cone harvesting in dense forests to mitigate the safety and inefficiency of traditional manual harvesting. The suggested system combines multi-sensor fusion perception, variable-stiffness rigid-flexible composite manipulator, and smart path planning into a single aerial harvesting system. To create a three-dimensional model of the environment and robust cone detection under complicated lighting conditions and extreme canopy occlusion, a heterogeneous sensor suite such as LiDAR, depth cameras, and inertial sensors is used. According to the results of fused perception, collision-free approach paths are created to lead the UAV safely to target cones in limited three-dimensional spaces. One of the significant contributions of this work is the iterative design and optimization of a dedicated harvesting manipulator to be used in aerial forestry operations. A comparative analysis of various structural designs leads to the creation of a rigid flexible composite manipulator with an effective workspace diameter of 1.8 m and adequate stiffness to reduce the effects of the downwash of the UAV rotor. The disturbance-assisted harvesting strategy is adopted by the system, which enables efficient dislodgement of cones without requiring accurate grasping. The proposed technical route is proven to be feasible based on laboratory experiments and initial field tests carried out in real forest settings. It has been experimentally proven that the combined system can effectively perform autonomous harvesting cycles, including target recognition, navigation, and cone dislodgement, thus offering a practical technical paradigm of intelligent and safe forestry harvesting applications.