Toward Autonomous Exploration in Confined Underwater Environments

Abstract

In this field note we detail the operations and discuss the results of an experiment conducted in the unstructured environment of an underwater cave complex, using an autonomous underwater vehicle (AUV). For this experiment the AUV was equipped with two acoustic sonar to simultaneously map the caves' horizontal and vertical surfaces. Although the caves' spatial complexity required AUV guidance by a diver, this field deployment successfully demonstrates a scan matching algorithm in a simultaneous localization and map- * The author can be also reached at Computer Vision and Robotics Institute, Universitat de Girona, 17003, Girona, Spain, amallios@eia.udg.edu.ping (SLAM) framework that significantly reduces and bounds the localization error for fully autonomous navigation. These methods are generalizable for AUV exploration in confined underwater environments where surfacing or pre-deployment of localization equipment are not feasible and may provide a useful step toward AUV utilization as a response tool in confined underwater disaster areas.

Attitude-Trajectory Estimation for Forward-Looking Multibeam Sonar Based on Acoustic Image Registration

“…While there are many technologies to assist in navigation for land or air based vehicles, these technologies do not necessarily transfer well to the underwater environment. Global Positioning System (GPS) may be referenced using underwater acoustic beacons [1], however a system may not always be available, or the accuracy good enough, for tasks such as exploration [2] or underwater inspection [3] [4]. Although inertial navigation systems are unaffected by being underwater, they are costly and subject to drift [5].…”

Inspection of an underwater structure using point‐cloud SLAM with an AUV and a laser scanner

“…Regarding acoustic SLAM, the literature presents solutions for 2D as well as 3D. While in 2D, some studies focus on feature‐based SLAM (Ribas, Ridao, Domingo, & Neira, ), others use featureless methods because in a natural environment, features are much more difficult to extract robustly than in a man‐made environment (Burguera, González, & Oliver, ; Mallios, Ridao, Ribas, Carreras, & Camilli, ; Vallicrosa & Ridao, ). In this way, 3D underwater acoustic SLAM has focused on featureless approaches for the same reason (Fairfield, Kantor, & Wettergreen, ; Roman & Singh, ; Barkby, Williams, Pizarro, & Jakuba, ; Palomer, Ridao, & Ribas, ).…”

“…Regarding acoustic SLAM, the literature presents solutions for 2D as well as 3D. While in 2D, some studies focus on feature-based SLAM (Ribas, Ridao, Domingo, & Neira, 2008), others use featureless methods because in a natural environment, features are much more difficult to extract robustly than in a man-made environment (Burguera, González, & Oliver, 2012;Mallios, Ridao, Ribas, Carreras, & Camilli, 2015;Vallicrosa & Ridao, 2018). In this way, 3D…”

Efficient Autonomous Robotic Exploration With Semantic Road Map in Indoor Environments

“…A large number of related approaches are developed to cope with different aspects of the autonomous exploration problem [4]. In this section, we mainly focus on three tightly coupled aspects that our framework is built upon in the autonomous exploration.…”