Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/91804
Title: Multi-AUV motion planning for archeological site mapping and photogrammetric reconstruction
Authors: Wu, Jane
Bingham, Russell C.
Ting, Samantha
Yager, Kolton
Wood, Zoe J.
Gambin, Timmy
Clark, Christopher M.
Keywords: Autonomous underwater vehicles
Underwater archaeology
Photogrammetry -- Digital techniques
Sonar
Three-dimensional modeling
Issue Date: 2019
Publisher: John Wiley & Sons, Inc.
Citation: Wu, J., Bingham, R. C., Ting, S., Yager, K., Wood, Z. J., Gambin, T., & Clark, C. M. (2019). Multi‐AUV motion planning for archeological site mapping and photogrammetric reconstruction. Journal of Field Robotics, 36(7), 1250-1269.
Abstract: This paper presents coupled and decoupled multi-autonomous underwater vehicle (AUV) motion planning approaches for maximizing information gain. The work is motivated by applications in which multiple AUVs are tasked with obtaining video footage for the photogrammetric reconstruction of underwater archeological sites. Each AUV is equipped with a video camera and side-scan sonar. The side-scan sonar is used to initially collect low-resolution data to construct an information map of the site. Coupled and decoupled motion planning approaches with respect to this map are presented. Both planning methods seek to generate multi-AUV trajectories that capture close-up video footage of a site from a variety of different viewpoints, building on prior work in single-AUV rapidly exploring random tree (RRT) motion planning. The coupled and decoupled planners are compared in simulation. In addition, the multiple AUV trajectories constructed by each planner were executed at archeological sites located off the coast of Malta, albeit by a single-AUV due to limited resources. Specifically, each AUV trajectory for a plan was executed in sequence instead of simultaneously. Modifications are also made by both planners to a baseline RRT algorithm. The results of the paper present a number of trade-offs between the two planning approaches and demonstrate a large improvement in map coverage efficiency and runtime.
URI: https://www.um.edu.mt/library/oar/handle/123456789/91804
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