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Multi-vehicle teams are being used more and more frequently to solve increasingly complex problems [1, 2]. In order for the team to work effectively, the vehicles must communicate to coordinate their efforts. In applications with high quality communication links, the vehicles are able to operate almost as a single entity. But in more harsh and dynamic environments, such as underwater, communication...
Advanced approaches to intelligent, real-time decision making are difficult to test for multi-agent systems. Specifically, the expense and logistics of fielding multiple unmanned underwater vehicles in an open ocean environment are significant challenges in marine autonomy. Traditionally, algorithms may be developed and tested under ideal conditions with tools that do not accurately reflect real-time...
Environmental monitoring of spatially-distributed geo-physical processes (e.g., temperature, pressure, or humidity) requires efficient sampling schemes, particularly, when employing an autonomous mobile agent to execute the sampling task. Many approaches have considered optimal sampling strategies which specialize in minimizing estimation error, while others emphasize reducing resource usage, yet...
With the advent of new technologies, robotic surveying systems are being developed to facilitate the collection of ground-based information to validate and complement data collected by traditional and satellite-based instruments. The development of such systems necessitates an accurate set of reference data. Given the limitations of current in situ measurement methods to aid remote sensing, this paper...
Efficiently measuring environmental phenomena (e.g., elevation, chemical composition, and mineral density) is a task typically reserved for the geoscience community. Recent robotic systems with the potential for addressing the task of sampling currently exist, yet their navigation strategies (and subsequently sampling strategies) are seldom a function of the spatial change in the measured phenomena...
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