Mapping Complex Marine Environments with Autonomous Surface Craft

This paper presents a novel marine mapping system using an Autonomous Surface Craft (ASC). The platform includes an extensive sensor suite for mapping environments both above and below the water surface. A relatively small hull size and shallow draft permits operation in cluttered and shallow environments. We address the Simultaneous Mapping and Localization (SLAM) problem for concurrent mapping above and below the water in large scale marine environments. Our key algorithmic contributions include: (1) methods to account for degradation of GPS in close proximity to bridges or foliage canopies and (2) scalable systems for management of large volumes of sensor data to allow for consistent online mapping under limited physical memory. Experimental results are presented to demonstrate the approach for mapping selected structures along the Charles River in Boston.United States. Office of Naval Research (N00014-06-10043)United States. Office of Naval Research (N00014-05-10244)United States. Office of Naval Research (N00014-07-11102)Massachusetts Institute of Technology. Sea Grant College Program (grant 2007-R/RCM-20

Towards three-dimensional underwater mapping without odometry

This paper presents a method for the creation of three-dimensional maps of underwater cisterns and wells using a submersible robot equipped with two scanning sonars and a compass. Previous work in this area utilized a particle filter to perform offline simultaneous localization and mapping (SLAM) in two dimensions using a single sonar [11]. This work utilizes scan matching and incorporates an additional sonar that scans in a perpendicular plane. Given a set of overlapping horizontal and vertical sonar scans, an algorithm was implemented to map underwater chambers by matching sets of scans using a weighted iterative closest point (ICP) method. This matching process has been augmented to align the features of the underwater cistern data without robot odometry. Results from a swimming pool and an archeological site trials indicate successful mapping is achieved

The Malta cistern mapping project : expedition II

This paper documents the second of two archeological expeditions that employed several underwater robot mapping and localization techniques. The goal of this project is to explore and map ancient cisterns located on the islands of Malta and Gozo. Dating back to 300 B.C., the cisterns of interest acted as water storage systems for fortresses, private homes, and churches. They often consisted of several connected chambers, still containing water. A Remotely Operated Vehicle (ROV), was deployed into cisterns to obtain video and sonar images. Using a variety of sonar based mapping techniques, two-dimensional maps of 18 different cisterns were created.peer-reviewe

Mapping and visualizing ancient water storage systems with an ROV - an approach based on fusing stationary scans within a particle filter

This paper presents a new method for construct- ing 2D maps of enclosed underwater structures using an underwater robot equipped with only a 2D scanning sonar, compass and depth sensor. In particular, no motion model or odometry is used. To accomplish this, a two step offline SLAM method is applied to a set of stationary sonar scans. In the first step, the change in position of the robot between each consecutive pair of stationary sonar scans is estimated using a particle filter. This set of pair wise relative scan positions is used to create an estimate of each scan’s position within a global coordinate frame using a weighted least squares fit that optimizes consistency between the relative positions of the entire set of scans. In the second step of the method, scans and their estimated positions act as inputs to a mapping algorithm that constructs 2D octree-based evidence grid maps of the site. This work is motivated by a multi-year archeological project that aims to construct maps of ancient water storage systems, i.e. cisterns, on the islands of Malta and Gozo. Cisterns, wells, and water galleries within fortresses, churches and homes oper- ated as water storage systems as far back as 2000 B.C. Using a Remotely Operated Vehicle (ROV) these water storage systems located around the islands were explored while collecting video, still images, sonar, depth, and compass measurements. Data gathered from 3 different expeditions has produced maps of over 60 sites. Presented are results from applying the new mapping method to both a swimming pool of known size and to several of the previously unexplored water storage systems.peer-reviewe

Underwater robots with sonar and smart tether for underground cistern mapping and exploration

This paper describes the application of using a submersible remotely operated vehicle (ROV) to map and explore underground water cisterns during a series of expeditions to Malta and Gozo. The purpose of this project was to create maps of ancient cisterns located under private homes, churches, and fortresses where passageways leading to the cisterns are too narrow and dangerous for humans to enter. These cisterns were used as water storage systems for hundreds of years, and many still contained water. The small ROV that was lowered into these cisterns was equipped with a sonar module to enable the creation of maps, two cameras to record live video, a grabber-arm for interacting with objects in the environment, and a Smart Tether to record additional positioning data of the ROV. Each of these components are discussed in terms of functionality and appropriateness for use by archaeologists wishing to explore and extract mapping information from narrow water-filled caverns. Additionally, three different mapping and localization techniques are presented including 1) Sonar image mosaics using stationary sonar scans, 2) Sonar image mosaics using stationary sonar scans with Smart Tether position data, and 3) Simultaneous Localization and Mapping (SLAM) using stationary sonar scans. Each of the algorithms used in this project have benefits in certain applications. During two expeditions in Malta and Gozo, 2-dimensional maps of 32 cisterns were successfully constructed.peer-reviewe

Toward autonomous exploration in confined underwater environments

Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Journal of Field Robotics 33 (2016): 994-1012, doi:10.1002/rob.21640.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 mapping (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.This research work was partially sponsored by the EU FP7-Projects: Tecniospring- Marie Curie (TECSPR13-1-0052), MORPH (FP7-ICT-2011-7-288704), Eurofleets2 (FP7-INF-2012-312762), and the National Science Foundation (OCE-0955674)

Archaeology via underwater robots : mapping and localization within Maltese cistern systems

This paper documents the application of several underwater robot mapping and localization techniques used during an archaeological expedition. The goal of this project was to explore and map ancient cisterns located on the islands of Malta and Gozo. The cisterns of interest acted as water storage systems for fortresses, private homes, and churches. They often consisted of several connected chambers, still containing water. A sonar-equipped Remotely Operated Vehicle (ROV) was deployed into these cisterns to obtain both video footage and sonar range measurements. Four different mapping and localization techniques were employed including 1) Sonar image mosaics using stationary sonar scans, and 2) Simultaneous Localization and Mapping (SLAM) while the vehicle was in motion, 3) SLAM using stationary sonar scans, and 4) Localization using previously created maps. Two dimensional maps of 6 different cisterns were successfully constructed. It is estimated that the cisterns were built as far back as 300 B.C.peer-reviewe

Surface Reconstruction of Maltese Cisterns Using ROV Sonar Data for Archeological Study

Abstract. We present a methodology and algorithm for the reconstruc tion of three dimensional geometric models of ancient Maltese water stor age systems, i.e. cisterns, from sonar data. This project was conducted as a part of a four week expedition on the islands of Malta and Gozo. During this expedition, investigators used underwater robot systems ca pable of mapping ancient underwater cisterns and tunnels. The mapping included probabilistic algorithms for constructing the maps of the sonar data and computer graphics for surface reconstruction and visualization. This paper presents the general methodology for the data acquisition and the novel application of algorithms from computer graphics for surface reconstruction to this new data setting. In addition to reconstructing the geometry of the cisterns, the visualization system includes methods to enhance the understanding of the data by visualizing water level and texture detail either through the application of real image data via pro jective textures or by more standard texture mapping techniques. The resulting surface reconstructions and visualizations can be used by ar chaeologists for educational purposes and to help understand the shape and history of such water receptacles

Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications, and witnessing a steady transition of this technology to industry. We survey the current state of SLAM. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers. This paper simultaneously serves as a position paper and tutorial to those who are users of SLAM. By looking at the published research with a critical eye, we delineate open challenges and new research issues, that still deserve careful scientific investigation. The paper also contains the authors' take on two questions that often animate discussions during robotics conferences: Do robots need SLAM? and Is SLAM solved