{"title":"Telemetry for AUVs","authors":"J. Alves, Konstantinos Pelekanakis, R. Petroccia","doi":"10.1049/sbra525e_ch9","DOIUrl":"https://doi.org/10.1049/sbra525e_ch9","url":null,"abstract":"In this chapter, we introduce the topic of telemetry for autonomous underwater vehicles (AUVs) and draw considerations on different techniques and approaches to be used when establishing underwater communications.","PeriodicalId":126968,"journal":{"name":"Autonomous Underwater Vehicles: Design and practice","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114545725","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}
Tahiya Salam, D. Kularatne, Eric Forgoston, M. A. Hsieh
{"title":"Adaptive sampling and energy-efficient navigation in time-varying flows","authors":"Tahiya Salam, D. Kularatne, Eric Forgoston, M. A. Hsieh","doi":"10.1049/sbra525e_ch18","DOIUrl":"https://doi.org/10.1049/sbra525e_ch18","url":null,"abstract":"This chapter presents a strategy to enable a team of mobile robots to adaptively sample and track a dynamic spatiotemporal process. We propose a distributed strategy where robots collect sparse sensor measurements, create a reduced -order model (ROM) of the spatiotemporal process, and use this model to estimate field values for areas without sensor measurements of the dynamic process. The robots then use these estimates of the field, or inferences about the process, to adapt the model and reconfigure their sensing locations. We use this method to obtain an estimate for the underlying fl ow field and use that to plan optimal energy paths for robots to travel between sensing locations. We show that the errors due to the reduced -order modeling scheme are bounded, and we illustrate the application of the proposed solution in simulation and compare it to centralized and global approaches. We then test our approach with physical marine robots sampling a spatially nonuniform time -varying process in a water tank.","PeriodicalId":126968,"journal":{"name":"Autonomous Underwater Vehicles: Design and practice","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130661029","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}
Signe A. Redfield, Elizabeth I. Leonard, J. Lennon
{"title":"Task specification and behavior verification for UUV behavior design","authors":"Signe A. Redfield, Elizabeth I. Leonard, J. Lennon","doi":"10.1049/sbra525e_ch14","DOIUrl":"https://doi.org/10.1049/sbra525e_ch14","url":null,"abstract":"The robotics community is deeply interested in both platform design and behavior design, but we lack tools to connect the two. The platform, the behavior design, and the environment work together to determine the robot's actions, but our tools visualize the design of the hardware and the design of the behaviors separately. We lack tools that allow us to visualize the relationship between the platform and the behavior. To address this gap, we introduce a new design method based on a tabular representation called Capability Analysis Tables. The Capability Analysis Table enables the designer to define the constraints on a behavior design based on the platform it will be used on, and to define the constraints on the platform based on the behavior design. It gives the customer and the designer an opportunity to more clearly specify the desired behavior. Environmental factors are implicit in the platform interface definitions -sensory perception filters environmental inputs (colored objects can only be seen by sensors that produce color information) and actuators filter environmental outputs. Communications are handled explicitly as outputs and as either operator inputs or remotely gathered sensory data.","PeriodicalId":126968,"journal":{"name":"Autonomous Underwater Vehicles: Design and practice","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133163069","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}
{"title":"Summary, conclusions, and future work","authors":"F. Ehlers","doi":"10.1049/sbra525e_ch19","DOIUrl":"https://doi.org/10.1049/sbra525e_ch19","url":null,"abstract":"The chapter elaborates on three views on the maritime robotics aspect of AUVs (autonomous underwater vehicles). Summaries, conclusions, and recommendations for future work from the authors of the chapters are collected. The conclusion from a (holistic) viewpoint on autonomy is given. AUVs belong to the class of unmanned or automated systems, which are removing or remotely locating the operator. This reduces cost of the operation, reduces the size of the platform, and removes risk of life because the maritime operation is a naturally harsh environment. In this sense, AUVs can be viewed as maritime robots. However, AUVs can be (much!) more. They can interactively adapt to their environment, which is a sign of autonomy. On-board processing power will allow them to adapt with machine speed. Sufficient processing power is a prerequisite for implementing learning algorithms on board the AUVs in order to improve with experience, but to apply this learning advances in the organisation of the learning space are needed.","PeriodicalId":126968,"journal":{"name":"Autonomous Underwater Vehicles: Design and practice","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133910164","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}
E. Maehle, Benjamin Meyer, Cedric Isokeit, Ulrich Behrje
{"title":"MONSUN: a swarmAUV for environmental monitoring and inspection","authors":"E. Maehle, Benjamin Meyer, Cedric Isokeit, Ulrich Behrje","doi":"10.1049/sbra525e_ch12","DOIUrl":"https://doi.org/10.1049/sbra525e_ch12","url":null,"abstract":"This chapter presents the development of the small swarm -capable autonomous underwater vehicle (AUV) MONSUN and its use for environmental monitoring and inspection tasks. A summarizing description of robot development in hardware and software is given, whereby efforts of the design process are explained in detail. After the focus on underwater communication techniques, swarm behaviours based on robust and scaleable localization principles are presented. Finally, the flexibility and functionality of the system are shown with the help of various experiments and field tests.","PeriodicalId":126968,"journal":{"name":"Autonomous Underwater Vehicles: Design and practice","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114338083","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}
{"title":"Data compression, data association and reduced complexity SLAM techniques for UUVs during transit","authors":"A. Sarma","doi":"10.1049/sbra525e_ch7","DOIUrl":"https://doi.org/10.1049/sbra525e_ch7","url":null,"abstract":"In the transiting stage of an unmanned undersea vehicle (UUV) mission, it is of interest to minimize platform localization error with minimal processing. Earlier work [1] derived a simultaneous localization and map building (SLAM) -inspired estimator of platform location and velocity, dubbed \"velocity -over -ground\" (VOG)-SLAM, that provides virtually identical performance in transit scenarios as conventional SLAM. The method lends itself to simple real-time operation as map building is not required. The \"VOG\" simplification was devised based on (a) the observation that the second measurement of a persistent contact was required for potential performance improvement in SLAM and (b) the intuitive idea that SLAM is providing velocity information since contact measurements can only be relative to the platform. We provide here a direct argument by arguing its optimality properties via connection to the maximum likelihood estimator (MLE). In addition, techniques for sonar data processing, measurement generation and data association methodologies to determine proper assignments between measurements and persistent bottom features are discussed. These further extend concepts found in [2]. The process can be currently completed before the next ping arrives suggesting near real-time SLAM performance in complex undersea environments","PeriodicalId":126968,"journal":{"name":"Autonomous Underwater Vehicles: Design and practice","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122597828","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}
{"title":"Adaptive–robust control of autonomous underwater vehicle with unknown system dynamics","authors":"Spandan Roy, S. Roy, I. Kar","doi":"10.1049/sbra525e_ch4","DOIUrl":"https://doi.org/10.1049/sbra525e_ch4","url":null,"abstract":"This chapter introduces a new class of ARC tracking control framework for AUV without any knowledge of the system dynamics parameters. Conventional ARC strategies either require complete/partial knowledge of the systems dynamics parameters or presume the overall uncertainty (or its time derivative) is upper bounded by a constant. However, such presumption is restrictive for systems like AUV which has explicit presence of states in its structure of system uncertainty.Besides, many of the existing AR-based designs suffer from the over-and underestimation problems of switching gains. In such regards, the proposed ASRC law not only avoids restrictive presumptions of system uncertainty being upper bounded by a constant, it simultaneously alleviates the over-and underestimation problems of switching gain. Futher, the effectiveness of the ASRC law is verified in simulation in comparison with the existing ASMC law under the scenario of uncertain system dynamics. An important future work would be to formulate an ARC for AUV considering input/output delay since data acquisition and localization in underwater scenario is always challenging and a controller needs to take care of such circumstances.","PeriodicalId":126968,"journal":{"name":"Autonomous Underwater Vehicles: Design and practice","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130704984","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}