Exploring the potential of collaborative UAV 3D mapping in Kenyan savanna for wildlife research
This work addresses conservation challenges for researchers by improving UAV-based habitat mapping, but it appears incremental as it compares existing methods without reporting specific performance gains.
The study tackled the problem of 3D mapping for wildlife research in Kenyan savannas by exploring collaborative UAV frameworks, comparing V-SLAM and SfM with standard offline approaches to optimize data acquisition.
UAV-based biodiversity conservation applications have exhibited many data acquisition advantages for researchers. UAV platforms with embedded data processing hardware can support conservation challenges through 3D habitat mapping, surveillance and monitoring solutions. High-quality real-time scene reconstruction as well as real-time UAV localization can optimize the exploration vs exploitation balance of single or collaborative mission. In this work, we explore the potential of two collaborative frameworks - Visual Simultaneous Localization and Mapping (V-SLAM) and Structure-from-Motion (SfM) for 3D mapping purposes and compare results with standard offline approaches.