Cooperative vehicle control, feature tracking and ocean sampling
Edward Fiorelli · 2005
This dissertation concerns the development of a feedback control framework for coordinat-ing multiple, sensor-equipped, autonomous vehicles into mobile sensing arrays to perform adaptive sampling of observed fields. The use of feedback is central; it maintains the array, i.e. regulates formation position, orientation, and shape, and directs the array to perform its sampling mission in response to measurements taken by each vehicle. Specifically, we address how to perform autonomous gradient tracking and feature detection in an unknown field such as temperature or salinity in the ocean. Artificial potentials and virtual bodies are used to coordinate the autonomous vehicles, modelled as point masses (with unit mass). The virtual bodies consist of linked, moving reference points called virtual leaders. Artificial potentials couple the dynamics of the vehicles and the virtual bodies. The dynamics of the virtual body are then prescribed allowing the virtual body, and thus the vehicle group, to perform maneuvers that include translation, rotation and contraction/expansion, while ensuring that the formation error remains bounded. This methodology is called the Virtual Body and Artificial Potential