Zhang, Guoxiang (University of California, Merced), Shang, Bo (Northeastern University, Shenyang), Chen, YangQuan (University of California, Merced), Moyes, Holley (University of California, Merced)

SmartCaveDrone: 3D Cave Mapping Using UAVs As Robotic Co-Archaeologists

Scheduled for presentation during the "Sensor Fusion - II" (ThB5), Thursday, June 15, 2017, 14:45−15:05, San Marco Island

2017 International Conference on Unmanned Aircraft Systems, June 13-16, 2017, Miami Marriott Biscayne Bay, Miami, FL,

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

This paper proposes the concept of drones capable of functioning as “Co-Archaeologists” that can map large caves and enter dangerous or hard-to-reach spaces. Using RGB-D data collected by drones, we will be able to produce accurate 3D models and semantic maps with proper lighting co-supervised by human archaeologists. This is going to be a major advance in archaeological practice, which can accelerate the speed of archaeological exploits by extending the archaeologists’ sight and perception range. This will enable us to conduct 3D analyses so that we may answer new questions and create new insights into the archaeological record. The archaeologists will be able to visualize data collected by drones and instruct the drones’ next step in real-time. These data will also be important in site management, data sharing and visualization. Human/drone interaction becomes important, not only for operating the equipment, but also for guiding drones to areas of interest to be mapped. Maps or real-time “fly-throughs” only make sense when they are organized by human interaction with the space. This human interaction is vital when visualizing and understanding a space and should be reflected in the imagery. We envision that this technology will be game changing in cave mapping and pertinent to anyone rendering interior spaces. It creates longer term impacts in archaeology and digital heritage and potentially creates a transformative way for further enhancing the performance of 3D mapping.