Date of Original Version
Abstract or Table of Contents
We are developing a multi-robot science exploration architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF uses a group of robotic boats (the OASIS platforms) to enable in-situ study of ocean surface 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). The TAOSF 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 to range from autonomous control to teleoperated control. In this manner, TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for tasking, control, and monitoring. It combines and extends prior related work done by the authors and their institutions. The TAOSF architecture is applicable to other areas where multiple sensing assets are needed, including ecological forecasting, water management, carbon management, disaster management, coastal management, homeland security, and planetary exploration. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). Several components of the TAOSF system have been tested, including the OASIS boats, the communications and control interfaces between the various hardware and software subsystems, and an airborne sensor validation system. Field tests in support of future HAB characterization were performed under controlled conditions, using rhodamine dye as a HAB simulant that was dispersed in a pond. In this paper, we describe the overall TAOSF architecture and its components, discuss the initial tests conducted and outline the next steps.