Kjetil Bergh Ånonsen

• Thio, Vincent Martello Kwie Hoe; Aparicio, Joaquin; Ånonsen, Kjetil Bergh & Bekkeng, Jan Kenneth (2021). Experimental Evaluation of the Forkbeard Ultrasonic Indoor Positioning System. IEEE Transactions on Instrumentation and Measurement. ISSN 0018-9456. doi: 10.1109/TIM.2021.3136261. Full text in Research Archive Show summary

  Indoor positioning systems are crucial to provide location based services in areas that are not covered by a Global Navigation Satellite System. Among the many technologies applied to this field, ultrasound has emerged as a potential low-cost, high-accuracy approach to positioning based on trilateration. Several ultrasonic systems have been proposed over the years. Of these, academic systems are typically prototypes that are unavailable to the public, whereas commercial systems generally do not provide characterization test results. In this work, we have conducted a detailed characterization study of a commercial indoor positioning system for smart devices developed by Forkbeard Technologies AS. We tested the system under static and dynamic conditions in a motion capture lab of approximately 150 m2. We considered different room occupancies, beacon configurations, and device positions. The results, given in terms of 2D absolute errors at different confidence levels, show great variation depending on the aforementioned conditions. The worst case scenario corresponds to a pedestrian in motion in an office setup with 4 beacons, with the phone placed in the pocket. In this case, 80% of the errors were below 143 cm. The best results were obtained under static conditions using 10 beacons, for which 80% of the errors were below 44 cm.

• Thio, Vincent Martello Kwie Hoe; Aparicio, Joaquin; Ånonsen, Kjetil Bergh; Bekkeng, Jan Kenneth & Booij, Wilfred (2021). Fusing of a continuous output PDR algorithm with an ultrasonic positioning system. IEEE Sensors Journal. ISSN 1530-437X. doi: 10.1109/JSEN.2021.3134468. Full text in Research Archive Show summary

  The availability of inertial navigation sensors in smartphones has facilitated the development of pedestrian dead reckoning (PDR) models on a large scale. These models often consist of a step detection algorithm combined with a heading estimation routine. Common approaches to step detection include searching for peaks/valleys in the acceleration signal, principle frequency estimation, and machine learning techniques. Since the sensors embedded in smart devices are prone to noise, the position error grows unbounded if unchecked and requires periodical corrections based on external measurements. In this work, we propose a novel step detection algorithm based on sine-wave approximation of the acceleration signal. This method detects step fractions as well as full steps, which allows for continuous and real-time updates. The step detection algorithm is combined with a heading estimation routine described in our previous work to obtain a stand-alone PDR model. To mitigate error accumulation, we fuse the proposed model with position and heading measurements provided by a commercial indoor positioning system based on ultrasound. We evaluate the performance of the PDR and fused model in an open office environment, by walking along a trajectory while carrying a smartphone in hand or in the pocket. The results demonstrate the feasibility of the sine-wave approximation approach to step detection, as well as the expected benefits of fusing PDR with the ultrasonic system.

• Thio, Vincent; Ånonsen, Kjetil Bergh & Bekkeng, Jan Kenneth (2021). Relative Heading Estimation for Pedestrians Based on the Gravity Vector. IEEE Sensors Journal. ISSN 1530-437X. doi: 10.1109/JSEN.2021.3052430. Full text in Research Archive Show summary

  Inertial navigation of pedestrians carrying a smart device is a core component of many indoor positioning systems. While infrastructure-based solutions typically depend on an installation of dedicated hardware, inertial navigation depends only on sensors embedded in the device itself. A single solution can thus be applied to a large range of use cases. This work focuses on one of the main challenges in inertial navigation: user heading estimation. We describe a complete statistical model for heading estimation based on the IMU and magnetometer, assuming a fixed device pose on the pedestrian. Our aim is to provide a stand-alone solution, suitable for direct implementation into a larger positioning framework. The method consists of two consecutive parts. The first focuses on gravity vector estimation based on IMU data. We describe a method for obtaining independent estimates under dynamic conditions, thereby removing the quasi-static initialization phase required by conventional methods. The second part combines the gravity vector with gyro and magnetic measurements to estimate user heading. The proposed method is tested against a motion capture system, and against an alternative method based on attitude. We find that both methods produce similar results in terms of accuracy.

• Hagen, Ove Kent & Ånonsen, Kjetil Bergh (2018). Terrain referenced navigation using sand dunes and sand ripples in presence of tides. OCEANS. ISSN 0197-7385. doi: 10.1109/OCEANS.2018.8604790. Full text in Research Archive Show summary

  We investigated using terrain referenced navigationin shallow water in the presence of unknown tide, with anautonomous underwater vehicle equipped with a high resolutionbathymetric sensor. The mission area had both variations, withlarge sand dunes, and flatness with small sand ripples. In orderto deal with the unknown substantial tide and shallow water, wetested a non-linear estimator for horizontal position, tide level andsound speed errors, a four dimensional Rao-Blackwellized pointmass filter. The algorithm received an initial position estimatefrom the inertial navigation system (INS), computed the probabilitydensity function for the position and environmental errors,tested for convergence, and provided a Gaussian approximationthat could be used by the INS. The results showed that thealgorithm converged consistently in both areas, more often inthe sand dune area, but surprisingly with comparable to higheraccuracy in the sand ripple area. This demonstrated that terrainreferenced navigation worked as expected, on sand dunes, inshallow water with substantial tide. The flatness is sometimesonly a matter of scale, and this technique should be consideredused everywhere when equipped with high resolution sensors.

• Morrison, Aiden; Sokolova, Nadezda; Haavardsholm, Trym Vegard; Hagen, Ove Kent; Opsahl, Thomas Olsvik & Ånonsen, Kjetil Bergh [Show all 7 contributors for this article] (2017). Collaborative indoor navigation for emergency services personnel. IEEE Aerospace Conference. Proceedings. ISSN 1095-323X. 2017-June. doi: 10.1109/AERO.2017.7943729. Full text in Research Archive Show summary

  First responders and other emergency services personnel must often enter buildings which prevent the use of GPS or other satellite navigation signals for positioning. Loss of navigation capability combined with the fact that the buildings are often unknown to the personnel in question makes it more difficult for individual team members to coordinate with one another, and difficult or impossible for the team leader to monitor and direct the actions of each team member. While inertial navigation or pedestrian dead reckoning provide for some degree of navigation in GPS signal denied environments, these solutions degrade with time and may require prohibitively large and expensive inertial solutions to navigate over extended periods, while also allowing each individual user to accumulate independent positioning errors and thereby appearing to ‘drift away’ from one another. This paper presents an implementation of a collaborative navigation system utilizing each of user-to-user radio links, Global Navigation Satellite Systems (GNSS) when available, inertial navigation, pedestrian dead reckoning, as well as camera based Simultaneous Location and Mapping (SLAM) to provide a team of users with absolute and relative situational awareness for themselves and their team. The application of collaborative navigation to such a team provides the triple benefits of providing improved absolute navigation accuracy, improved relative navigation accuracy, and greatly enhanced situational awareness for all cooperating team members.

• Hagen, Ove Kent; Ånonsen, Kjetil Bergh & Sæbø, Torstein Olsmo (2015). Towards autonomous mapping with AUVs - Relative terrain navigation. OCEANS. ISSN 0197-7385. doi: 10.23919/oceans.2015.7404387. Full text in Research Archive
• Hagen, Ove Kent & Ånonsen, Kjetil Bergh (2014). Using terrain navigation to improve marine vessel navigation systems. Marine Technology Society journal. ISSN 0025-3324. 48(2), p. 45–58. doi: 10.4031/MTSJ.48.2.6. Full text in Research Archive
• Hagen, Ove Kent & Ånonsen, Kjetil Bergh (2013). Improving terrain navigation by concurrent tidal- and sound speed error estimation. OCEANS. ISSN 0197-7385. Full text in Research Archive
• Hagen, Ove Kent; Ånonsen, Kjetil Bergh & Skaugen, Atle (2013). Robust surface vessel navigation using terrain navigation. OCEANS. ISSN 0197-7385. doi: 10.1109/oceans-bergen.2013.6608055. Full text in Research Archive
• Hagen, Ove Kent; Ånonsen, Kjetil Bergh & Sæbø, Torstein Olsmo (2012). Low-Altitude Terrain Navigation for Underwater Vehicles - Integration of an Interferometric Side Scan Sonar Improves Terrain Navigation in Low-Altitude Scenarios. Sea Technology. ISSN 0093-3651. 53(6), p. 10–13. Full text in Research Archive
• Hagen, Ove Kent; Ånonsen, Kjetil & Sæbø, Torstein Olsmo (2011). Low altitude auv terrain navigation using an interferometric sidescan sonar. OCEANS. ISSN 0197-7385. doi: 10.23919/oceans.2011.6107003. Full text in Research Archive
• Hagen, Ove Kent; Ånonsen, Kjetil & Mandt, Magne (2010). The HUGIN Real-Time Terrain Navigation System. OCEANS. ISSN 0197-7385. p. 1–7. doi: 10.1109/OCEANS.2010.5664579. Full text in Research Archive
• Ånonsen, Kjetil & Hagen, Ove Kent (2010). An Analysis of Real-Time Terrain Aided Navigation Results from a HUGIN AUV. OCEANS. ISSN 0197-7385. p. 1–9. doi: 10.1109/OCEANS.2010.5664076. Full text in Research Archive

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• Ånonsen, Kjetil Bergh & Hagen, Ove Kent (2022). Terrain navigation techniques for AUV MCM operations. Full text in Research Archive
• Ånonsen, Kjetil Bergh & Mandt, Magne (2022). Water Referenced Doppler Velocity Aiding for AUV Navigation. OCEANS. ISSN 0197-7385. Full text in Research Archive
• Ånonsen, Kjetil Bergh & Mandt, Magne (2022). Water Referenced Doppler Velocity Aiding for AUV Navigation. Full text in Research Archive
• Ånonsen, Kjetil Bergh; Gade, Kenneth & Hagen, Ove Kent (2020). AUV navigation: challenges and solutions. In Ehlers, Frank (Eds.), Autonomous Underwater Vehicles: Design and Practice. The Institution of Engineering and Technology. ISSN 9781785617034. p. 105–143. Full text in Research Archive
• Hagen, Ove Kent & Ånonsen, Kjetil Bergh (2018). Terrain referenced navigation using sand dunes and sand ripples in precense of tides. Full text in Research Archive
• Ånonsen, Kjetil Bergh; Hagen, Ove Kent & Berglund, Einar (2017). Autonomous Mapping with AUVs Using Relative Terrain Navigation. Full text in Research Archive
• Morrison, Aiden; Sokolova, Nadezda; Haavardsholm, Trym Vegard; Hagen, Ove Kent; Opsahl, Thomas Olsvik & Ånonsen, Kjetil Bergh [Show all 7 contributors for this article] (2017). Collaborative indoor navigation for emergency services personnel. Full text in Research Archive
• Morrison, Aiden; Haavardsholm, Trym Vegard; Hagen, Ove Kent; Opsahl, Thomas Olsvik; Ånonsen, Kjetil Bergh & Eriksen, Erik Holthe (2017). Collaborative Indoor Navigation for Emergency Services Personnel. Full text in Research Archive
• Hagen, Ove Kent & Ånonsen, Kjetil Bergh (2016). On the performance of terrain navigation. Full text in Research Archive
• Hagen, Ove Kent; Ånonsen, Kjetil Bergh & Sæbø, Torstein Olsmo (2015). Towards autonomous mapping with AUVs - Relative terrain navigation. Full text in Research Archive
• Ånonsen, Kjetil Bergh & Hagen, Ove Kent (2013). The HUGIN AUV terrain navigation module. Full text in Research Archive
• Hagen, Ove Kent & Ånonsen, Kjetil Bergh (2013). Improving terrain navigation by concurrent tidal- and sound speed error estimation. Full text in Research Archive
• Hagen, Ove Kent; Ånonsen, Kjetil Bergh & Skaugen, Atle (2013). Robust surface vessel navigation using terrain navigation. Full text in Research Archive
• Ånonsen, Kjetil & Hagen, Ove Kent (2011). Recent developments in the HUGIN AUV terrain navigation system. Full text in Research Archive
• Hagen, Ove Kent; Ånonsen, Kjetil & Sæbø, Torstein Olsmo (2011). Low altitude auv terrain navigation using an interferometric sidescan sonar. Full text in Research Archive
• Ånonsen, Kjetil Bergh & Hagen, Ove Kent (2010). An Analysis of Real-Time Terrain Navigation Results from a HUGIN AUV. Full text in Research Archive
• Hagen, Ove Kent; Ånonsen, Kjetil Bergh & Mandt, Magne (2010). The HUGIN Real-Time Terrain Navigation System. Full text in Research Archive
• Berglund, Einar; Ånonsen, Kjetil; Gade, Kenneth & Hagen, Ove Kent (2009). The HUGIN navigation system. Full text in Research Archive
• Ånonsen, Kjetil Bergh & Hagen, Ove Kent (2009). Terrain aided underwater navigation using pockmarks. Full text in Research Archive Show summary

  Terrain aided navigation techniques are attractive for obtaining submerged position fixes for an underwater vehicle. However, their use is dependent on a certain degree of variation in the terrain. This paper investigates the performance of terrain navigation algorithms in an area with pockmarks, i.e. craters in the sea bed formed by expulsion of gas or water from the sediments. We use real terrain data from an area with pockmarks, together with simulated vehicle and multibeam echo sounder measurements, to investigate the behavior of the terrain navigation techniques in the area. The simulations indicate that this type of terrain is suitable for terrain aided navigation. The pockmarks also seem to be sufficiently different to provide unique fixes. As pockmarks often occur in flat terrain, traditionally thought of as not suited for terrain navigation, the use of pockmarks facilities terrain navigation in a number of new applications.

• Nornes, Stein Melvær; Sørensen, Asgeir Johan; Ludvigsen, Martin; Johnsen, Geir; Schjølberg, Ingrid & Ånonsen, Kjetil Bergh (2018). Guidance and Control of Marine Robotics for Ocean Mapping and Monitoring. Norges teknisk-naturvitenskapelige universitet. ISSN 9788232631957. Full text in Research Archive Show summary

  The ocean is an integral part of life on Earth, both as a source of food and oxygen, a medium of transportation and a major influence on weather and climate. Unfortunately, proper management and preservation of the ocean depend on knowledge we do not necessarily possess, due to what oceanographers refer to as a “century of undersampling”. Autonomous marine robotic platforms are showing promising steps towards increasing the quantity and quality of ocean mapping and monitoring. This thesis concerns development of methods for motion control and mapping systems for marine robotic platforms with varying levels of autonomy. The main motivation of the work has been to increase the level of autonomy of the systems, in order to reduce costs and the need for human interaction, while simultaneously increasing recording efficiency and data quality. The research questions guiding the work are focused on how marine robotic platforms with increasing levels of autonomy can improve the quality, quantity and efficiency of ocean mapping and monitoring, both in terms of data collection and interpretation. The thesis presents contributions to different modules of an overarching autonomy architecture. The primary task of a marine robotic platform during a mapping mission is to bring one or more payload sensors to the appropriate locations in time and space. The motion of the platform must be efficient in order to record the desired quantity of data, and accurate in order to achieve the desired quality of data. Sensors such as underwater optical cameras, benefit from a methodical motion pattern and a constant distance to the area of interest (AOI), both for data quality and area coverage. This work presents an automated relative motion control strategy for mapping steep underwater structures using a Remotely Operated Vehicle (ROV). The strategy employs a Doppler Velocity Logger (DVL) oriented in the viewing direction of the cameras to maintain a stable distance to the AOI, ensuring high image quality. Through several full-scale experiments, the strategy is demonstrated to efficiently record high quality datasets of challenging structures. A major benefit of autonomous platforms is the ability to operate in scenarios that are deemed too dull, distant or dangerous for human operators. This work presents the results from several mapping missions performed with marine robotic platforms on multiple scientific cruises. Photogrammetry surveys that require highly accurate control over prolonged periods of time demonstrate situations where operator fatigue would have led to a gradual decrease in performance of a manual system. Arctic operations in the polar night that require measurements that are not polluted by artificial light exemplify scenarios which would have been impossible to perform within safety regulations for crewed vessels. In order to approach a truly autonomous system, the system must be able to acquire and analyze the information necessary to make informed decisions. In this work, underwater hyperspectral imaging (UHI) is demonstrated to be a promising tool for high-resolution seafloor exploration and classification. The increased spectral information present in UHI-data compared to regular RGB-imagery is well suited for computer analysis and online classification of objects of interest. Autonomous inspection of seafloor structures or other AOIs poses interesting opportunities for both industry and marine science. This work presents experimental results from an ROV implementation of a behavior- and reactive based autonomy architecture. The architecture is able to conduct a realistic mission from surface launch to target area with obstacle avoidance. The work is motivated by the needs of the end-users in the marine sciences, and involves interdisciplinary collaboration, in particular between the fields of marine control systems, marine biology and marine archaeology. The developed methods are applied to real world cases on a variety of scientific cruises, primarily in the Trondheimsfjord from the NTNU-owned and operated R/V Gunnerus, but also in the Arctic on the UiT R/V Helmer Hanssen and in the Pacific on the Geomar R/V Sonne. The thesis is edited as a collection of papers.

• Ånonsen, Kjetil (2010). Advances in Terrain Aided Navigation for Underwater Vehicles. Norges teknisk-naturvitenskapelige universitet. ISSN 9788247122143. Full text in Research Archive Show summary

  This thesis deals with the subject of terrain aided underwater navigation for underwater vehicles. The term “navigation” is throughout the thesis understood as the task of estimating the position and attitude of a vehicle, together with the corresponding uncertainties. The main focus is on autonomous underwater vehicles (AUVs), but the methods discussed can also be readily used by other underwater vehicles. Terrain aided navigation is an attractive concept for obtaining submerged position fixes for the main navigation system, in most cases an inertial navigation system, for which the deterioration of the position accuracy necessitates external aiding methods. Terrain navigation has been used for decades in land and air applications, e.g. in aircraft and cruise missiles. In recent years, the technique has been applied also in underwater vehicles. The thesis concentrates on what is known as “bathymetric terrain navigation”, in which bathymetric measurements are matched directly with a map, as opposed to the related area of “feature-based navigation”, in which features extracted from the bottom measurements are used for position updates. Throughout the thesis, the terrain navigation system is treated as an external module, providing measurement updates for the main navigation system in a loosely coupled manner. This approach makes the terrain navigation module more portable and the overall system more robust to errors in the terrain navigation updates, although it is more difficult to exploit the internal states of the main navigation system in the terrain navigation algorithm. The thesis starts with a recapitulation of existing methods for terrain navigation (Chapter 2), with focus on Bayesian estimation methods. The problem is formulated as a recursive state-space estimation problem, which is highly nonlinear, due to the nonlinear nature of the terrain measurement function. As a consequence, nonlinear estimation methods like point mass filters (PMFs), particle filters (PFs) and sigma point Kalman filters (SPKFs) must be used. Special emphasis is put on the fact that, due to the computational complexity of the estimation methods, one must often use lowdimensional state-space models, leading to discrepancies between the true system and the filter model. Such discrepancies sometimes lead to inaccuracies and overconfidence in the estimators. Chapter 3 continues with a discussion on the special difficulties that arise when using terrain navigation techniques underwater, e.g. different sensor characteristics, the effect of tide compensation etc. It is also shown how unknown depth biases can be handled, either through estimation of the bias in the filter, or by using relative depth information only. A novel formulation of the filter process model is also developed, in an attempt to model the drift in the main navigation system more accurately. Chapter 4 gives an overview of map databases, which are essential to the success of terrain navigation. The main contributions of the thesis are related to the computational results presented in Chapter 5. The behavior in different terrain types of the TERCOM (Terrain Contour Matching) algorithm, the PMF algorithm, various particle filters and the SPKF are compared, using sea data from an AUV equipped with a multibeam echosounder. All the tested methods are able to estimate the position of the AUV with an accuracy within the horizontal resolution of the terrain map, with the PMF as the most accurate and robust, though also the most computationally demanding, method. A clear positive effect on accuracy and robustness from the inclusion of the depth bias is observed. The main problem with the methods discussed in the thesis is their tendency of overconfidence, i.e. the estimated uncertainty is too low compared to the true uncertainty. This can be partially solved by sub-sampling the terrain measurements, minimizing the effect of unmodeled correlations. Results from computations using the novel process model derived in Chapter 3 show that this approach does not solve the inconsistency problem, though the accuracy and stability are slightly improved on the tested data. Chapter 5 closes with some simulations using a map database based on real MBE data from an area with pockmarks, i.e. small craters on the sea floor. The sea floor in the area is otherwise flat. The simulations indicate that the pockmarks contain enough terrain information to facilitate the use of terrain navigation in areas previously thought of as unsuited

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