A Review on Viewpoints and Path Planning for UAV-Based 3-D Reconstruction

Unmanned aerial vehicles (UAVs) are widely used platforms to carry data capturing sensors for various applications. The reason for this success can be found in many aspects: the high maneuverability of the UAVs, the capability of performing autonomous data acquisition, flying at different heights, and the possibility to reach almost any vantage point. The selection of appropriate viewpoints and planning the optimum trajectories of UAVs is an emerging topic that aims at increasing the automation, efficiency, and reliability of the data capturing process to achieve a dataset with desired quality. On the other hand, 3-D reconstruction using the data captured by UAVs is also attracting attention in research and industry. This article investigates a wide range of model-free and model-based algorithms for viewpoints and path planning for 3-D reconstruction of large-scale objects. It presents a bibliography of more than 200 references to cover different aspects of the topic. The analyzed approaches are limited to those that employ a single-UAV as a data capturing platform for outdoor 3-D reconstruction purposes. In addition to discussing the evaluation strategies, this article also highlights the innovations and limitations of the investigated approaches. It concludes with a critical analysis of the existing challenges and future research perspectives.

Automated summary

Unmanned aerial vehicles (UAVs) are popular platforms for data capturing due to their high maneuverability, autonomous data acquisition capability, and ability to reach difficult vantage points. This article explores a wide range of algorithmic approaches for viewpoints and path planning in 3-D reconstruction using UAV-captured data. With over 200 references, it covers different aspects of the topic and focuses on single-UAV outdoor 3-D reconstruction. The article discusses evaluation strategies, highlights innovations and limitations, and provides a critical analysis of existing challenges and future research perspectives.