Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778706
B. Claus, J. Kinsey, Yogesh A. Girdhar
This work describes the ongoing effort to derive methods to collectively direct a heterogeneous group of vehicles trajectories, velocities, communication rates and sampling rates by the navigational accuracy required, energy consumption, communication performance and observational goals. These methods are being experimentally validated through field trials during the Summer and Fall of 2016. Initial results demonstrate the utility of using fine scale regional oceanographic models as a tool to locate features of interest; inform the spatial extents, bandwidth and power usage of both satellite and acoustic communication methods; and provide data on the performance and energy usage of the acoustically aided and dead-reckoned navigation methods.
{"title":"Towards persistent cooperative marine robotics","authors":"B. Claus, J. Kinsey, Yogesh A. Girdhar","doi":"10.1109/AUV.2016.7778706","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778706","url":null,"abstract":"This work describes the ongoing effort to derive methods to collectively direct a heterogeneous group of vehicles trajectories, velocities, communication rates and sampling rates by the navigational accuracy required, energy consumption, communication performance and observational goals. These methods are being experimentally validated through field trials during the Summer and Fall of 2016. Initial results demonstrate the utility of using fine scale regional oceanographic models as a tool to locate features of interest; inform the spatial extents, bandwidth and power usage of both satellite and acoustic communication methods; and provide data on the performance and energy usage of the acoustically aided and dead-reckoned navigation methods.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"93 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114021821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778708
M. Sasano, Shogo Inaba, Akihiro Okamoto, T. Seta, K. Tamura, T. Ura, Shinichi Sawada, Taku Suto
A new complex system of underwater positioning and communication has been developed for control of multiple autonomous underwater vehicles (AUVs). It consists of a semi-submersible autonomous surface vehicle (ASV), a hovering type AUV, and three surface buoys. The operational concepts for control of multiple AUVs are discussed.
{"title":"Development of a regional underwater positioning and communication system for control of multiple autonomous underwater vehicles","authors":"M. Sasano, Shogo Inaba, Akihiro Okamoto, T. Seta, K. Tamura, T. Ura, Shinichi Sawada, Taku Suto","doi":"10.1109/AUV.2016.7778708","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778708","url":null,"abstract":"A new complex system of underwater positioning and communication has been developed for control of multiple autonomous underwater vehicles (AUVs). It consists of a semi-submersible autonomous surface vehicle (ASV), a hovering type AUV, and three surface buoys. The operational concepts for control of multiple AUVs are discussed.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129878864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778723
T. Vikranth, Ch. Raghavendra, T. Surya Kumari
This type of vehicle can transform its shape and configuration depending on the task to be performed. Main purpose of AAUV is to complete a mission both on air and underwater. By combining exclusive features of multirotor and AUV research and surveillance tasks become simple. Once setting the GPS coordinates of specified area to be surveyed, the multi rotor vehicle will be activated and transforms itself to perform given task. After reaching particular GPS coordinate area; the multi rotor vehicle transforms itself in to an underwater vehicle and perform the given task, once the task is completed vehicle surfaces and reaches to home position. The communication from AAUV is supported by iridum satellite constellation and Rock block satellite communication module. This AAUV can fill its fuel form sea water through electrolysis process, Fuel cell and solar cells.
{"title":"Autonomous air & underwater vehicle","authors":"T. Vikranth, Ch. Raghavendra, T. Surya Kumari","doi":"10.1109/AUV.2016.7778723","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778723","url":null,"abstract":"This type of vehicle can transform its shape and configuration depending on the task to be performed. Main purpose of AAUV is to complete a mission both on air and underwater. By combining exclusive features of multirotor and AUV research and surveillance tasks become simple. Once setting the GPS coordinates of specified area to be surveyed, the multi rotor vehicle will be activated and transforms itself to perform given task. After reaching particular GPS coordinate area; the multi rotor vehicle transforms itself in to an underwater vehicle and perform the given task, once the task is completed vehicle surfaces and reaches to home position. The communication from AAUV is supported by iridum satellite constellation and Rock block satellite communication module. This AAUV can fill its fuel form sea water through electrolysis process, Fuel cell and solar cells.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128260776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778707
A. Kukulya, R. Stokey, Carl Fiester, Edgar Mauricio Hoyos Padilla, G. Skomal
In recent years, great technological subsurface advancements have been made to observe and study Carcharodon carcharias, white sharks with autonomous underwater vehicles (AUVs) [1]. Prior to 2011, tracking pelagic predators like sharks was limited to using active tracking from boats [2] and passive acoustic arrays [3]. These aforementioned techniques proved to be limited by logistics such as weather and boat maneuverability as well as providing poor spatial resolution since fish movements were mimicked by the tracking vessel.
{"title":"Multi-vehicle autonomous tracking and filming of white sharks Carcharodon carcharias","authors":"A. Kukulya, R. Stokey, Carl Fiester, Edgar Mauricio Hoyos Padilla, G. Skomal","doi":"10.1109/AUV.2016.7778707","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778707","url":null,"abstract":"In recent years, great technological subsurface advancements have been made to observe and study Carcharodon carcharias, white sharks with autonomous underwater vehicles (AUVs) [1]. Prior to 2011, tracking pelagic predators like sharks was limited to using active tracking from boats [2] and passive acoustic arrays [3]. These aforementioned techniques proved to be limited by logistics such as weather and boat maneuverability as well as providing poor spatial resolution since fish movements were mimicked by the tracking vessel.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124550994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778681
Eirik Hexeberg Henriksen, I. Schjølberg, Tor Berge Gjersvik
This paper presents an open-source simulation environment for underwater vehicles and robots. The simulation environment allows the user to simulate underwater robotic vehicles with realistic dynamic behavior in a 3-dimensional virtual environment. The environment is highly configurable, and offers a set of modules for simulating different types of vehicles in a number of underwater scenarios. The simulator can be used for control system development, path planning, risk management and testing in a safe virtual environment. The possibility for virtual testing will lower the cost and reduce time of operations. The simulation environment is an expansion of MORSE - Modular Open Robots Simulation Engine. The modular nature of MORSE allows the user to easily configure the simulations, making new environments and robots, as well as adding sensor and control interfaces. This expansion includes modules for hydrodynamic simulation, thrusters and underwater sensors. These modules enables the user to make a virtual replica of a specific underwater robot system. Such replica may be used as a Software-in-the-loop system for testing and verification of control systems and algorithms. The simulation environment allows interaction with a large set of robotic middlewares.
{"title":"UW MORSE: The underwater Modular Open Robot Simulation Engine","authors":"Eirik Hexeberg Henriksen, I. Schjølberg, Tor Berge Gjersvik","doi":"10.1109/AUV.2016.7778681","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778681","url":null,"abstract":"This paper presents an open-source simulation environment for underwater vehicles and robots. The simulation environment allows the user to simulate underwater robotic vehicles with realistic dynamic behavior in a 3-dimensional virtual environment. The environment is highly configurable, and offers a set of modules for simulating different types of vehicles in a number of underwater scenarios. The simulator can be used for control system development, path planning, risk management and testing in a safe virtual environment. The possibility for virtual testing will lower the cost and reduce time of operations. The simulation environment is an expansion of MORSE - Modular Open Robots Simulation Engine. The modular nature of MORSE allows the user to easily configure the simulations, making new environments and robots, as well as adding sensor and control interfaces. This expansion includes modules for hydrodynamic simulation, thrusters and underwater sensors. These modules enables the user to make a virtual replica of a specific underwater robot system. Such replica may be used as a Software-in-the-loop system for testing and verification of control systems and algorithms. The simulation environment allows interaction with a large set of robotic middlewares.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127288511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778656
Mingxi Zhou, R. Bachmayer, B. deYoung
A Slocum underwater glider is been modified to map the underside of icebergs for monitoring iceberg deterioration off the coast of Newfoundland, Canada. The vehicle is equipped with a mechanical scanning sonar to map the iceberg surface, and a thruster for level-flight at a higher surging speed. In this paper we are presenting a profile-following controller that uses the sonar ranges to compute desired headings guiding the Slocum glider traveling safely around icebergs. A vehicle-attached occupancy map (VOM) is updated using sonar measured ranges with a dynamic inverse-sonar model. A desired path is then generated from the VOM by applying polynomial regression on the occupied cells. The line-of-sight guidance law is implemented to compute the desired heading to follow the desired path. The algorithm is initially evaluated in a simulation environment. The vehicle operation is simulated on a real-time hardware simulator, while the sonar is modeled in ray-tracing method. The iceberg is derived from an iceberg database with additional translational and rotational motion emulating a floating iceberg. After that, the guidance system is applied on a set of field data collected in 2015. During the trial, the Slocum glider was deployed to profile an underwater ramp feature in Conception Bay, Newfoundland, Canada. The feasibility of the porposed controller is indicated by the outcomes from this paper.
{"title":"Towards autonomous underwater iceberg profiling using a mechanical scanning sonar on a underwater Slocum glider","authors":"Mingxi Zhou, R. Bachmayer, B. deYoung","doi":"10.1109/AUV.2016.7778656","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778656","url":null,"abstract":"A Slocum underwater glider is been modified to map the underside of icebergs for monitoring iceberg deterioration off the coast of Newfoundland, Canada. The vehicle is equipped with a mechanical scanning sonar to map the iceberg surface, and a thruster for level-flight at a higher surging speed. In this paper we are presenting a profile-following controller that uses the sonar ranges to compute desired headings guiding the Slocum glider traveling safely around icebergs. A vehicle-attached occupancy map (VOM) is updated using sonar measured ranges with a dynamic inverse-sonar model. A desired path is then generated from the VOM by applying polynomial regression on the occupied cells. The line-of-sight guidance law is implemented to compute the desired heading to follow the desired path. The algorithm is initially evaluated in a simulation environment. The vehicle operation is simulated on a real-time hardware simulator, while the sonar is modeled in ray-tracing method. The iceberg is derived from an iceberg database with additional translational and rotational motion emulating a floating iceberg. After that, the guidance system is applied on a set of field data collected in 2015. During the trial, the Slocum glider was deployed to profile an underwater ramp feature in Conception Bay, Newfoundland, Canada. The feasibility of the porposed controller is indicated by the outcomes from this paper.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129137994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778704
H. Yoshida, S. Ishibashi, Ohta Yutaka, M. Sugesawa, Kiyotaka Tanaka
This paper discusses the concept design of a long term underwater observation system utilizing an AUV and described two key technologies to develop a practical system.
本文讨论了利用水下航行器的长期水下观测系统的概念设计，并描述了实现该系统的两个关键技术。
{"title":"A concept design of underwater docking robot and development of its fundamental technologies","authors":"H. Yoshida, S. Ishibashi, Ohta Yutaka, M. Sugesawa, Kiyotaka Tanaka","doi":"10.1109/AUV.2016.7778704","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778704","url":null,"abstract":"This paper discusses the concept design of a long term underwater observation system utilizing an AUV and described two key technologies to develop a practical system.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"136 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131222715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778680
C. Kaiser, D. Yoerger, J. Kinsey, Sean Kelley, A. Billings, Justin Fujii, S. Suman, M. Jakuba, Z. Berkowitz, C. German, A. Bowen
The Autonomous Underwater Vehicle (AUV) Sentry has been in routine operation since 2009. It is a 6000m depth rated autonomous survey and sampling platform and is a “fly-away” system meaning it transports easily anywhere in the world to utilize vessels of opportunity. Sentry, initially a radical concept and experiment in AUV design, is now the AUV component of the National Deep Submergence Facility (NDSF) operated by Woods Hole Oceanographic Institution and as such spends up to 200 days per year in the field conducting operations for ocean scientists. Accordingly, Sentry must be reliable enough for a customer focused mission, but flexible enough to undertake previously unconceived missions on very short notice and with a high success rate. Field operations on a “Global Class” research vessel can easily exceed $100,000 per day placing a premium on efficiency. Here we describe not only the vehicle Sentry, but also, the systems and infrastructure which supports Sentry and the unique nature of operations within the NDSF.
{"title":"The design and 200 day per year operation of the Autonomous Underwater Vehicle Sentry","authors":"C. Kaiser, D. Yoerger, J. Kinsey, Sean Kelley, A. Billings, Justin Fujii, S. Suman, M. Jakuba, Z. Berkowitz, C. German, A. Bowen","doi":"10.1109/AUV.2016.7778680","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778680","url":null,"abstract":"The Autonomous Underwater Vehicle (AUV) Sentry has been in routine operation since 2009. It is a 6000m depth rated autonomous survey and sampling platform and is a “fly-away” system meaning it transports easily anywhere in the world to utilize vessels of opportunity. Sentry, initially a radical concept and experiment in AUV design, is now the AUV component of the National Deep Submergence Facility (NDSF) operated by Woods Hole Oceanographic Institution and as such spends up to 200 days per year in the field conducting operations for ocean scientists. Accordingly, Sentry must be reliable enough for a customer focused mission, but flexible enough to undertake previously unconceived missions on very short notice and with a high success rate. Field operations on a “Global Class” research vessel can easily exceed $100,000 per day placing a premium on efficiency. Here we describe not only the vehicle Sentry, but also, the systems and infrastructure which supports Sentry and the unique nature of operations within the NDSF.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128190754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778662
Matias Valdenegro-Toro
Object detection and recognition are typically stages that form part of the perception module of Autonomous Underwater Vehicles, used with different sensors such as Sonar and Optical imaging, but their design is usually separate and they are only combined at test time. In this work we present a convolutional neural network that does both object detection (through detection proposals) and recognition in Forward-Looking Sonar images and is trained with bounding boxes and class labels only. Convolutional layers are shared and a 128-element feature vector is shared between both tasks. After training we obtain 93% correct detections and 75% accuracy, but accuracy can be improved by fine-tuning the classifier sub-network with the generated detection proposals. We evaluated fine-tuning with a SVM classifier trained on the shared feature vector, increasing accuracy to 85%. Our detection proposal method can also detect unlabeled and untrained objects, and has good generalization performance. Our unified method can be used in any kind of sonar image, does not make assumptions about an object's shadow, and learns features directly from data.
{"title":"End-to-end object detection and recognition in forward-looking sonar images with convolutional neural networks","authors":"Matias Valdenegro-Toro","doi":"10.1109/AUV.2016.7778662","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778662","url":null,"abstract":"Object detection and recognition are typically stages that form part of the perception module of Autonomous Underwater Vehicles, used with different sensors such as Sonar and Optical imaging, but their design is usually separate and they are only combined at test time. In this work we present a convolutional neural network that does both object detection (through detection proposals) and recognition in Forward-Looking Sonar images and is trained with bounding boxes and class labels only. Convolutional layers are shared and a 128-element feature vector is shared between both tasks. After training we obtain 93% correct detections and 75% accuracy, but accuracy can be improved by fine-tuning the classifier sub-network with the generated detection proposals. We evaluated fine-tuning with a SVM classifier trained on the shared feature vector, increasing accuracy to 85%. Our detection proposal method can also detect unlabeled and untrained objects, and has good generalization performance. Our unified method can be used in any kind of sonar image, does not make assumptions about an object's shadow, and learns features directly from data.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128629560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/AUV.2016.7778657
D. Bandara, Z. Leong, H. Nguyen, S. Jayasinghe, A. Forrest
Approximately 12% of the world's oceans are covered by ice. Understanding the physical processes, ecosystem structure, mixing dynamics and the role of these inaccessible environments in the context of global climate change is extremely important. Autonomous Underwater Vehicles (AUVs) play a major role in the potential exploration of these water systems due to the challenges of human access and relatively high associated risk. That said, AUV navigation and localization is challenging in these environments due to the unavoidable growth of navigational drift associated with inertial navigation systems, especially in long range missions under ice where surfacing in open water is not possible. While acoustic transponders have been used, they are time consuming and difficult to deploy. Terrain Relative Navigation (TRN) and Simultaneous Localization and Mapping (SLAM) based technologies are emerging in recent years as promising navigation solutions as they neither require deploying navigational aids or calculating the distance travelled from a reference point to determine location. One of the key challenges of underwater or under-ice image based localization results from the unstructured nature and lack of significant features in underwater environments. This issue has motivated the review presented in this paper, which outlines a potential area of under-ice AUV navigation and localization by combining TRN and SLAM with image matching methods for navigation in featureless environments.
{"title":"Technologies for under-ice AUV navigation","authors":"D. Bandara, Z. Leong, H. Nguyen, S. Jayasinghe, A. Forrest","doi":"10.1109/AUV.2016.7778657","DOIUrl":"https://doi.org/10.1109/AUV.2016.7778657","url":null,"abstract":"Approximately 12% of the world's oceans are covered by ice. Understanding the physical processes, ecosystem structure, mixing dynamics and the role of these inaccessible environments in the context of global climate change is extremely important. Autonomous Underwater Vehicles (AUVs) play a major role in the potential exploration of these water systems due to the challenges of human access and relatively high associated risk. That said, AUV navigation and localization is challenging in these environments due to the unavoidable growth of navigational drift associated with inertial navigation systems, especially in long range missions under ice where surfacing in open water is not possible. While acoustic transponders have been used, they are time consuming and difficult to deploy. Terrain Relative Navigation (TRN) and Simultaneous Localization and Mapping (SLAM) based technologies are emerging in recent years as promising navigation solutions as they neither require deploying navigational aids or calculating the distance travelled from a reference point to determine location. One of the key challenges of underwater or under-ice image based localization results from the unstructured nature and lack of significant features in underwater environments. This issue has motivated the review presented in this paper, which outlines a potential area of under-ice AUV navigation and localization by combining TRN and SLAM with image matching methods for navigation in featureless environments.","PeriodicalId":416057,"journal":{"name":"2016 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122348207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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