Abstract
Cranes play a significant role in transporting goods from one point to another in construction sites, factories, shipping yards, and mining sites. The main control objective of the cranes is to effectively convey the goods, including chemicals and sensitive materials, as quickly as possible without persistent oscillations. However, the trolley positioning and payload oscillation control have been challenging due to the flexibility of the cable carrying the goods and the nature of the cranes, particularly the rotation of tower cranes. This dataset provides trajectories and the corresponding payload oscillations for tower cranes using a laboratory-scaled setup, which covers the possible operating scenarios of the crane, including tower rotation, changing trolley trajectories, different payload mass and shapes, varying cable lengths, and payload hoisting. This data provides a valuable resource for understanding the dynamic behaviour of tower cranes and to train machine learning-based approaches for efficient control and automation of the cranes.