Sea Captains' Views on Automated Ship Route Optimization in Ice-covered Waters

Safety in ice-covered polar waters can be optimised via the choice of a ship's route. This is of utmost importance for conventional as well as autonomous ships. However, the current state of the art in e-Navigation tools has left two open questions. First, what essential information are these tools still missing, and second, how they are seen by sea captains. In order to address these questions, we organised an ice navigation workshop to systematically collect routing justifications given by and waypoints planned by experienced sea captains that are particularly seasoned in ice navigation. Here, we report the outcome of that workshop. Our key findings include the reasoning and the commentary of the participants in looking for a better and safer route. These comments shed light upon both the official and unofficial code of conduct in open waters and boil down into a list of additional prerequisite information if further steps towards system autonomy are sought. Finally, the expert-planned waypoints are to be published alongside this paper to act as a benchmark for future maritime studies

Exploring GNSS crowdsourcing feasibility: Combinations of measurements for modeling smartphone and higher end GNSS receiver performance

GNSS receiver data crowdsourcing is of interest for multiple applications, e.g., weather monitoring. The bottleneck in this technology is the quality of the GNSS receivers. Therefore, we lay out in an introductory manner the steps to estimate the performance of an arbitrary GNSS receiver via the measurement errors related to its instrumentation. Specifically, we do not need to know the position of the receiver antenna, which allows also for the assessment of smartphone GNSS receivers having integrated antennas. Moreover, the method is independent of atmospheric errors so that no ionospheric or tropospheric correction services provided by base stations are needed. Error models for performance evaluation can be calculated from receiver RINEX (receiver independent exchange format)data using only ephemeris corrections. For the results, we present the quality of different receiver grades through parametrized error models that are likely to be helpful in stochastic modeling, e.g., for Kalman filters, and in assessing GNSS receiver qualities for crowdsourcing applications. Currently, the typical positioning precision for the latest smartphone receivers is around the decimeter level, while for a professional-grade receiver, it is within a few millimeters

Towards tropospheric delay estimation using GNSS smartphone receiver network

Information on the water vapor distribution of the troposphere is useful for weather monitoring and forecast. Water vapor distribution can be estimated from tropospheric delays produced by high-grade Global Navigation Satellite System (GNSS) receivers. This type of techniques is currently used in the data assimilation process of Numerical Weather Prediction (NWP) models, especially, for the limited areas covered by these high-grade GNSS networks. We consider a new collaborative crowdsourcing-based alternative for obtaining these GNSS meteorology measurements. It relies on a GNSS smartphone receiver network, and hence promises to expand the use of GNSS meteorology techniques into areas not covered by high-end receiver networks. In order to assess the feasibility of estimating the troposphere water vapor distribution using such receiver networks, it is proposed a system architecture that supports the troposphere water vapor distribution estimation using a smartphone network. Next, it is presented the simulator test-bed that has been developed to emulate the proposed system in a representative way and to assess the system performances. The main motivation behind the simulator is that it provides a controlled environment for testing our method

Finding safe and efficient shipping routes in ice-covered waters: A framework and a model

Safety for conventional and autonomous navigation in ice-covered waters is a topic of rising importance. Here, we propose a generic extendable framework to provide the optimal route from multiple route planning objectives. These objectives are attained by an evaluation of multi-source input data, including state-of-the-art model data for ice conditions, for bathymetric knowledge, and for ship-ice interaction. Additionally, we model the ship-ship interactions statistically using a mean-field, to account for ships (indirectly) assisting each other via artificial ice channels. For the subsequent pathfinding problem, we propose a new A*-based algorithm that yields output which is not dependent on the grid format of the input data but instead consists of a path that follows the Earth's curvature. The outputs of the algorithm are a set of waypoints (representing the optimal route), the travel costs (expressed in time), and the additional travel cost estimates caused by route deviation, should the optimal route be altered in any way. The steaming speeds, the optimal route, and the deviation times are represented with two-dimensional (2D) maps. Finally, we provide a model implementation of our framework as a Matlab-package, ICEPATHFINDER, that is suitable for both operational and strategic ship route optimization

Design, Calibration, and Evaluation of a Backpack Indoor Mobile Mapping System

Indoor mobile mapping systems are important for a wide range of applications starting from disaster management to straightforward indoor navigation. This paper presents the design and performance of a low-cost backpack indoor mobile mapping system (ITC-IMMS) that utilizes a combination of laser range-finders (LRFs) to fully recover the 3D building model based on a feature-based simultaneous localization and mapping (SLAM) algorithm. Specifically, we use robust planar features. These are advantageous, because oftentimes the final representation of the indoor environment is wanted in a planar form, and oftentimes the walls in an indoor environment physically have planar shapes. In order to understand the potential accuracy of our indoor models and to assess the system’s ability to capture the geometry of indoor environments, we develop novel evaluation techniques. In contrast to the state-of-the-art evaluation methods that rely on ground truth data, our evaluation methods can check the internal consistency of the reconstructed map in the absence of any ground truth data. Additionally, the external consistency can be verified with the often available as-planned state map of the building. The results demonstrate that our backpack system can capture the geometry of the test areas with angle errors typically below 1.5° and errors in wall thickness around 1 cm. An optimal configuration for the sensors is determined through a set of experiments that makes use of the developed evaluation techniques

Indoor 3D: Overview on scanning and reconstruction methods

This chapter covers the essentials regarding indoor 3D data, from scanning to reconstruction. It is aimed for education and professionals. The order of presentation is background, history in measurement method development, sensors, sensor systems, positioning algorithms, reconstruction, and applications. The authors’ backgrounds are in indoor 3D, mobile laser scanning, indoor reconstruction, and robotics. In order to maintain a coherence in the text and provide some useful tools for the reader, we have selected to focus solely on the ICP version of simultaneous localization and mapping (SLAM). Regardless, this should give a solid base for the reader to understand other (e.g. probabilistic) indoor SLAM methods as well. Reconstruction algorithms (starting from room segmentation and opening detection) are discussed with the help of abundant figures. At the very end, we discuss future trends with a connection to the current applications and propose some exercise questions for students

Digital twin of a city: Review of technology serving city needs

Digital twins (DTs) have been found useful in manufacturing, construction, and maintenance. Adapting DTs to serve cities, the question arises of what an urban digital twin should contain and how it should be orchestrated to serve a city’s dynamical ecosystem, along with how to enhance the efficiency of the city. We are aligning with the commonplace idea that the main advantage of using DTs is economical as, for example, DTs can improve the planning of activities thus saving money and time. But how can they be useful for a city? Instead of looking at the DTs as solutions in search of problems to be solved, we start from city needs. Our approach is two-fold. We start by briefly reviewing existing possibilities for meeting some specific needs, but keep the focus on identifying and attempting to close the gap between the needs arising from everyday city functions and the latest DT techniques useful for meeting those needs. DTs are technically different and serve different applications, yet they share a common identity and name, as well as several technical similarities. Adopting computer science terminology, we see a back-end city DT as the container of all information, while any single front-end, visualized or used either by humans or robots, offers a limited but meaningful representation of the DT for a specific application. Alas, there are multiple open questions regarding the realization and benefits of such back-end DT. Nevertheless, we discuss how the back-end DT (or any specific DT) could be updated autonomously from sensor data using artificial intelligence techniques, and how the front-ends could be used for large benefits to the entire city ecosystem