{"title":"Hierarchical multi-agent command and control system for autonomous underwater vehicles","authors":"Tan Yew Teck, M. Chitre","doi":"10.1109/AUV.2012.6380760","DOIUrl":"https://doi.org/10.1109/AUV.2012.6380760","url":null,"abstract":"Inspired by the command structure of a manned submarine, we have developed a Command and Control (C2) system for autonomous underwater vehicles (AUVs) that allocates mission, navigation and vehicle tasks to individual self-contained agents, each with their own responsibilities and behaviors. These agents are distributed over different levels of control hierarchies where they behave deliberately at the supervisory level and reactively at the vehicle and navigational level. The collective interactions among the pool of agents enables the AUV to achieve its mission objectives autonomously. The mission supervisory level adopts a backseat driver paradigm where mission-level decisions are made based on the inputs provided by a pool of backseat driver (BD) agents. Each BD agent is responsible for handling different aspects of a mission and provides input in the form of mission points to achieve specific mission sub-tasks. This approach offers several advantages. Firstly, complex mission objectives can be divided into simpler mission sub-tasks and handled by different BD agents. Secondly, the C2 system's capabilities in coping with new mission scenarios can be easily extended through the introduction of new BD agents that generates the required maneuvering patterns. New mission behaviors may emerge from the cooperation and/or competition among the BD agents. These complex behaviors increase the level of mission autonomy. The C2 system described above is being used in the STARFISH AUVs and has been used to perform single AUV surveying missions as well as multi-AUV cooperative positioning missions.","PeriodicalId":340133,"journal":{"name":"2012 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128921982","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":"Undersea acoustic communication maps for collaborative navigation","authors":"D. Horner, G. Xie","doi":"10.1145/2398936.2398993","DOIUrl":"https://doi.org/10.1145/2398936.2398993","url":null,"abstract":"Communications play a key role in collaborative navigation algorithms. A better understanding of the ability to send and receive messages permits greater navigational flexibility and system robustness. This paper focuses on the building of an underwater acoustic communications map for collaborative navigation. The emphasis is in two areas - a local and global communications map. The local communications is defined with respect to a single destination reference point. Using a sample set of a priori signal to noise ratio acoustic modem data, Kriging techniques are used to create mean and variance map estimates. The global communications map is a compendium of local maps and is defined within a bounded survey space. Bayesian Inferencing is used for building the global map. It is based on REML parameter estimation of an anisotropic covariance function. The paper analyzes acoustic communication signal to noise datasets recently collected in Monterey Harbor, Monterey, CA and is used to demonstrate the above-described techniques.","PeriodicalId":340133,"journal":{"name":"2012 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124162140","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}
A. Phillips, J. Blake, S. Boyd, S. Ward, G. Griffiths
{"title":"Nature in Engineering for Monitoring the Oceans (NEMO): An isopycnal soft bodied approach for deep diving autonomous underwater vehicles","authors":"A. Phillips, J. Blake, S. Boyd, S. Ward, G. Griffiths","doi":"10.1109/AUV.2012.6380743","DOIUrl":"https://doi.org/10.1109/AUV.2012.6380743","url":null,"abstract":"Taking inspiration from nature the NEMOdeep vehicle described in this paper is being developed as a laboratory demonstrator to showcase potential technologies to achieve small deep diving autonomous underwater vehicles. The design of the vehicle is a hybrid of conventional AUV components with engineered analogues of marine animal organs. The internal structure is comprised of a spine, ribs and sternum, which support a hydrodynamic fairing or `skin'. The `brain' and actuators are developed using pressure tolerant electronics, negating the need for pressure vessels. The pressure tolerant electronics are surrounded by light mineral oil which transmits the hydrostatic pressure uniformly to the components while also providing buoyancy. The internal fluid is more compressible than seawater and the batteries and internal structure are less compressible than seawater: a `Buoyancy/Compressibility' organ is being developed to passively maintain neutral buoyancy over the 0 to 6000m depth range.","PeriodicalId":340133,"journal":{"name":"2012 IEEE/OES Autonomous Underwater Vehicles (AUV)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132618382","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}