The Telesupervised Adaptive Ocean Sensor Fleet

ABSTRACT We are developing a multi-robot science exploration architecture and system called the Telesupervised Adaptive OceanSensor Fleet (TAOSF). TAOSF uses a group of robotic boats (the OASIS platforms) to enable in-situ study of oceansurface and sub-surface phenomena. The OASIS boats are extended-deployment autonomous ocean surface vehicles,whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). TheTAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy.It allows multiple mobile sensing assets to function in a cooperative fashion, and the operating mode of the vessels torange from autonomous control to teleoperated control. In this manner, TAOSF increases data-gathering effectivenessand science return while reducing demands on scientists for tasking, control, and monitoring. It combines and extendsprior related work done by the authors and their institutions. The TAOSF architecture is applicable to other areas wheremultiple sensing assets are needed, including ecological forecasting, water management, carbon management, disastermanagement, coastal management, homeland security, and planetary exploration. The first field application chosen forTAOSF is the characterization of Harmful Algal Blooms (HABs). Several components of the TAOSF system have beentested, including the OASIS boats, the communications and control interfaces between the various hardware andsoftware subsystems, and an airborne sensor validation system. Field tests in support of future HAB characterizationwere performed under controlled conditions, using rhodamine dye as a HAB simulant that was dispersed in a pond. Inthis paper, we describe the overall TAOSF architecture and its components, discuss the initial tests conducted andoutline the next steps.Keywords: telesupervision, multirobot systems, sensor web, adaptive sampling, harmful algal blooms, ocean sensing.