Resumen
Modern plantation forest procedures still rely heavily on manual data acquisition in the inventory process, limiting the quantity and quality of the collected data. This limitation in collection performance is often due to the difficulty of traversing the plantation forest environment on foot. This work presents an autonomous system for exploring plantation forest environments using multi-rotor UAVs. The proposed method consists of three parts: waypoint selection, trajectory generation, and trajectory following. Waypoint selection is accomplished by estimating the rows? locations within the environment and selecting points between adjacent rows. Trajectory generation is completed using a non-linear optimization-based constant speed planner and the following is accomplished using a model predictive control approach. The proposed method is tested extensively in simulation against various procedurally generated forest environments, with results suggesting that it is robust against variations within the scene. Finally, flight testing is performed in a local plantation forest, demonstrating the successful application of our proposed method within a complex, uncontrolled environment.