1. |
- Andersson, Olov, 1979-, et al.
(author)
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WARA-PS : a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation
- 2021
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In: Autonomous Intelligent Systems. - : Springer Nature. - 2730-616X. ; 1:1
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Journal article (peer-reviewed)abstract
- A research arena (WARA-PS) for sensing, data fusion, user interaction, planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is presented. The objective is to demonstrate scientific discoveries and to generate new directions for future research on autonomous systems for societal challenges. The enabler is a computational infrastructure with a core system architecture for industrial and academic collaboration. This includes a control and command system together with a framework for planning and executing tasks for unmanned surface vehicles and aerial vehicles. The motivating application for the demonstration is marine search and rescue operations. A state-of-art delegation framework for the mission planning together with three specific applications is also presented. The first one concerns model predictive control for cooperative rendezvous of autonomous unmanned aerial and surface vehicles. The second project is about learning to make safe real-time decisions under uncertainty for autonomous vehicles, and the third one is on robust terrain-aided navigation through sensor fusion and virtual reality tele-operation to support a GPS-free positioning system in marine environments. The research results have been experimentally evaluated and demonstrated to industry and public sector audiences at a marine test facility. It would be most difficult to do experiments on this large scale without the WARA-PS research arena. Furthermore, these demonstrator activities have resulted in effective research dissemination with high public visibility, business impact and new research collaborations between academia and industry.
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2. |
- Lager, Mårten
(author)
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Digital Cognitive Companions for Marine Vessels : On the Path Towards Autonomous Ships
- 2021
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Doctoral thesis (other academic/artistic)abstract
- As for the automotive industry, industry and academia are making extensive efforts to create autonomous ships. The solutions for this are very technology-intense. Many building blocks, often relying on AI technology, need to work together to create a complete system that is safe and reliable to use. Even when the ships are fully unmanned, humans are still foreseen to guide the ships when unknown situations arise. This will be done through teleoperation systems.In this thesis, methods are presented to enhance the capability of two building blocks that are important for autonomous ships; a positioning system, and a system for teleoperation.The positioning system has been constructed to not rely on the Global Positioning System (GPS), as this system can be jammed or spoofed. Instead, it uses Bayesian calculations to compare the bottom depth and magnetic field measurements with known sea charts and magnetic field maps, in order to estimate the position. State-of-the-art techniques for this method typically use high-resolution maps. The problem is that there are hardly any high-resolution terrain maps available in the world. Hence we present a method using standard sea-charts. We compensate for the lower accuracy by using other domains, such as magnetic field intensity and bearings to landmarks. Using data from a field trial, we showed that the fusion method using multiple domains was more robust than using only one domain. In the second building block, we first investigated how 3D and VR approaches could support the remote operation of unmanned ships with a data connection with low throughput, by comparing respective graphical user interfaces (GUI) with a Baseline GUI following the currently applied interfaces in such contexts. Our findings show that both the 3D and VR approaches outperform the traditional approach significantly. We found the 3D GUI and VR GUI users to be better at reacting to potentially dangerous situations than the Baseline GUI users, and they could keep track of the surroundings more accurately. Building from this, we conducted a teleoperation user study using real-world data from a field-trial in the archipelago, where the users should assist the positioning system with bearings to landmarks. The users experienced the tool to give a good overview, and despite the connection with the low throughput, they managed through the GUI to significantly improve the positioning accuracy.
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3. |
- Lager, Mårten, et al.
(author)
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Long-Term Accuracy in Sea Navigation without using GNSS Systems
- 2017
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Conference paper (peer-reviewed)abstract
- Many ships today rely on Global Navigation Satellite System (GNSS), for their navigation, where GPS (Global Positioning System) is the most well known. Unfortunately, the GNSS systems make the ships dependent on external systems, which can be malfunctioning, be jammed or be spoofed. There are today some proposed techniques where, e.g. bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques , most often relying on high accuracy maps, with the accuracy of the navigational sensors being less important. Instead of relying on high accuracy maps and low accuracy navigation sensors, this paper presents an idea of the opposite, namely using low accuracy maps, but compensating this by using high accuracy navigational sensors and fusing data from both bottom depth measurements and magneticfield measurements.
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4. |
- Lager, Mårten, et al.
(author)
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Remote Operation of Unmanned Surface Vessel through Virtual Reality
- 2018
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Conference paper (peer-reviewed)abstract
- An unmanned ship can be designed without considering humancomfort, and can thus be constructed lighter, smaller and less expensive.It can carry out missions in rough terrain or be in areaswhere it would be dangerous for a human to operate. By not havingto support a crew, lengthy missions can be accepted, enabling, e.g.reconnaissance missions, or reducing emissions by lowering thespeed.Breakthroughs with autonomous systems enable more advancedunmanned surface vessels (USVs), but to be able to handle complexmissions in a dynamic environment, a human operator is stillassumed an effective decision maker. Thus, we propose a methodfor remote operation of a USV, where the operator uses VirtualReality (VR) to comprehend the surrounding environment. Greatimportance has been given to the ability to perform safe navigation,by designing a Graphical User Interface (GUI) that guides the operatorthrough the navigation process, by presenting the importantinformation at the right place in the right orientation.
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5. |
- Lager, Mårten, et al.
(author)
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Remote Supervision of an Autonomous Surface Vehicle using Virtual Reality
- 2019
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In: 10th IFAC Symposium on Intelligent Autonomous Vehicles IAV 2019 : Gdansk, Poland, 3–5 July 2019 - Gdansk, Poland, 3–5 July 2019. - : Elsevier BV. - 2405-8963. ; 52:8
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Conference paper (peer-reviewed)abstract
- We compared three different Graphical User Interfaces (GUI) that we have designed and implemented to enable human supervision of an Autonomous Surface Vehicle (ASV). Special attention has been paid to provide tools for a safe navigation and giving the user a good overall understanding of the surrounding world while keeping the cognitive load at a low level. Our findings indicate that a GUI in 3D, presented either on a screen or in a Virtual Reality (VR) setting provides several benefits compared to a Baseline GUI representing traditional tools.
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6. |
- Lager, Mårten, et al.
(author)
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Remote Supervision of an Unmanned Surface Vessel - a Comparison of Interfaces
- 2019
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In: 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). - 9781538685556
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Conference paper (peer-reviewed)abstract
- We compared three different Graphical User Interfaces (GUI) that we have designed and implemented to enable human supervision of an unmanned ship. Our findings indicate that a 3D GUI presented either on a screen or in a Virtual Reality (VR) setting provides several objective and subjective benefits compared to a Baseline GUI representing traditional tools.
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7. |
- Lager, Mårten, et al.
(author)
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Robust Terrain-Aided Navigation through Sensor Fusion
- 2020
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In: 23rd International Conference on Information Fusion Virtual Conference. - 9780578647098
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Conference paper (peer-reviewed)abstract
- To make autonomous, affordable ships feasible in the real world, they must be capable of safely navigating without fully relying on GPS, high-resolution 3D maps, or high-performance navigation sensors. We suggest a method for estimating the position using affordable navigation sensors (compass and speed log or inertial navigation sensor), sensors used for perception of the environment (cameras, echo sounder, magnetometer), and publicly available maps (sea charts and magnetic intensity anomalies maps). A real-world field trial has shown that the proposed fusion mechanism provides accurate and robust navigation, applicable for affordable autonomous ships.
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8. |
- Lager, Mårten
(author)
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Smart Technologies for Unmanned Surface Vessels : On the Path Towards Full Automation
- 2019. - 1
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Licentiate thesis (other academic/artistic)abstract
- As for the automotive industry, large efforts are being made by industry andacademia to create autonomous ships. Te solutions for this is very technologyintense, as many building blocks, often relying on AI technology, need to worktogether to create a complete system that is safe and reliable to use. Even whenthe ships are fully unmanned, humans are still foreseen to guide the ships whenunknown situations arise. Tis will be done through teleoperation systems.In this thesis, methods are presented to enhance the capability of two building blocks that are important for autonomous ships; a positioning system, and asystem for remote supervision.Te positioning system has been constructed to not rely on GPS (Global Positioning System), as this system can be jammed or be spoofed. Instead, it usesBayesian calculations to compare the bottom depth and magnetic field measurements with known sea charts and magnetic field maps, in order to estimate theposition. State-of-the-art techniques for this method normally use low-accuracynavigation sensors and high-resolution maps. Te problem is that there are hardlyany high-resolution maps available in the world, hence we present a method of theopposite; namely using high-accuracy navigation sensors and low-resolution maps(normal sea charts). Te results from a 20h test-run gave a mean position error of10.2m, which would in most cases be accurate enough for navigation purpose.In the second building block, we investigated, how 3D and VR approachescould support the remote operation of unmanned ships with a low bandwidthconnection, by comparing respective GUIs with a Baseline GUI following the currently applied interfaces in such contexts. Our findings show, that both the 3Dand VR approaches outperform the traditional approach significantly. We foundthe 3D GUI and VR GUI users to be better at reacting to potentially dangeroussituations compared to the Baseline GUI users, and they could keep track of thesurroundings more accurately.
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9. |
- Lager, Mårten, et al.
(author)
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Underwater terrain navigation during realistic scenarios
- 2018
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In: Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017. - Cham : Springer International Publishing. - 1876-1100 .- 1876-1119. - 9783319905082 ; 501, s. 186-209
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Conference paper (peer-reviewed)abstract
- Many ships today rely on Global Navigation Satellite Systems (GNSS), for their navigation, where GPS (Global Positioning System) is the most well-known. Unfortunately, the GNSS systems make the ships dependent on external systems, which can be malfunctioning, be jammed or be spoofed. There is today some proposed techniques where, e.g., bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques, most often relying on high-resolution maps, with the accuracy of the navigational sensors being less important. Instead of relying on high-resolution maps and low accuracy navigation sensors, this paper presents an implementation of the opposite, namely using low-resolution maps, but compensating this by using high-accuracy navigational sensors and fusing data from both bottom depth measurements and magnetic field measurements. A Particle Filter uses the data to estimate a position, and as a second step, a Kalman Filter enhances the accuracy even further. The algorithm has been tuned and evaluated using both a medium and a high-accuracy Inertial System. Comparisons of the various tuning methods are presented along with their performance results. The results from the simulated tests, described in this paper, show that for the high-end Inertial System, the mean position error is 10.2 m, and the maximum position error is 33.0 m during a 20 h test, which in most cases would be accurate enough to use for navigation.
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10. |
- Lager, Mårten, et al.
(author)
-
Underwater Terrain Navigation Using Standard Sea Charts and Magnetic Field Maps
- 2017
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In: 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI). - 9781509060634 - 9781509060641
-
Conference paper (peer-reviewed)abstract
- Many ships today rely on Global Navigation Satellite Systems (GNSS), for their navigation, where GPS (Global Positioning System) is the most well-known. Unfortunately, the GNSS systems make the ships dependent on external systems, which can be malfunctioning, be jammed or be spoofed. There are today some proposed techniques where, e.g., bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques, most often relying on high-resolution maps, with the accuracy of the navigational sensors being less important. Instead of relying on high-resolution maps and low accuracy navigation sensors, this paper presents an implementation of the opposite, namely using low-resolution maps, but compensating this by using high accuracy navigational sensors and fusing data from both bottom depth measurements and magnetic field measurements. The results from the simulated tests, described in this paper, show that the position error is below 25m throughout the whole test, and that the mean of the error is below 13m, which in most cases would be accurate enough to use for navigation.
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