TY - GEN
T1 - Towards Mapping of Underwater Structures by a Team of Autonomous Underwater Vehicles
AU - Xanthidis, Marios
AU - Joshi, Bharat
AU - Roznere, Monika
AU - Wang, Weihan
AU - Burgdorfer, Nathaniel
AU - Li, Alberto Quattrini
AU - Mordohai, Philippos
AU - Nelakuditi, Srihari
AU - Rekleitis, Ioannis
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - In this paper, we discuss how to effectively map an underwater structure with a team of robots considering the specific challenges posed by the underwater environment. The overarching goal of this work is to produce high-definition, accurate, photorealistic representation of underwater structures. Due to the many limitations of vision underwater, operating at a distance from the structure results in degraded images that lack details, while operating close to the structure increases the accumulated uncertainty due to the limited viewing area which causes drifting. We propose a multi-robot mapping framework that utilizes two types of robots: proximal observers which map close to the structure and distal observers which provide localization for proximal observers and bird’s-eye-view situational awareness. The paper presents the fundamental components and related current results from real shipwrecks and simulations necessary to enable the proposed framework, including robust state estimation, real-time 3D mapping, and active perception navigation strategies for the two types of robots. Then, the paper outlines interesting research directions and plans to have a completely integrated framework that allows robots to map in harsh environments.
AB - In this paper, we discuss how to effectively map an underwater structure with a team of robots considering the specific challenges posed by the underwater environment. The overarching goal of this work is to produce high-definition, accurate, photorealistic representation of underwater structures. Due to the many limitations of vision underwater, operating at a distance from the structure results in degraded images that lack details, while operating close to the structure increases the accumulated uncertainty due to the limited viewing area which causes drifting. We propose a multi-robot mapping framework that utilizes two types of robots: proximal observers which map close to the structure and distal observers which provide localization for proximal observers and bird’s-eye-view situational awareness. The paper presents the fundamental components and related current results from real shipwrecks and simulations necessary to enable the proposed framework, including robust state estimation, real-time 3D mapping, and active perception navigation strategies for the two types of robots. Then, the paper outlines interesting research directions and plans to have a completely integrated framework that allows robots to map in harsh environments.
KW - Localization
KW - Mapping
KW - Multi-robot
KW - Navigation
KW - Underwater
UR - http://www.scopus.com/inward/record.url?scp=85151053739&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85151053739&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-25555-7_12
DO - 10.1007/978-3-031-25555-7_12
M3 - Conference contribution
AN - SCOPUS:85151053739
SN - 9783031255540
T3 - Springer Proceedings in Advanced Robotics
SP - 170
EP - 185
BT - Robotics Research
A2 - Billard, Aude
A2 - Asfour, Tamim
A2 - Khatib, Oussama
T2 - 18th International Symposium of Robotics Research, ISRR 2022
Y2 - 25 September 2022 through 30 September 2022
ER -