All Outputs (2)

Learning to Explore: Unconstrained Indoor Exploration for Unmanned Aerial Vehicles using Representation Learning (2025)
Thesis
Chang, Y. (2025). Learning to Explore: Unconstrained Indoor Exploration for Unmanned Aerial Vehicles using Representation Learning. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/5292454

Unmanned Aerial Vehicles (UAVs) have been extensively used in various complex indoor environments due to their competitive spatial adaptability and manoeuvrability compared to Unmanned Ground Vehicles (UGVs). However, the inherent constraints of indo... Read More about Learning to Explore: Unconstrained Indoor Exploration for Unmanned Aerial Vehicles using Representation Learning.

The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation (2022)
Data
Chang, Y., Cheng, Y., Murray, J., Huang, S., & Shi, G. (2022). The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation. [Data]

The dataset contains image samples and Multi-task labels (i.e., regression and classification labels) collected from onboard UAV sensors in real-world indoor environments. By transforming the original labels following the instructions at: https://git... Read More about The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation.