Multi-AUV Control and Adaptive Sampling in Monterey Bay

Abstract

Abstract-Multi-AUV operations have much to offer a variety of underwater applications. With sensors to measure the environment and coordination that is appropriate to critical spatial and temporal scales, the group can perform important tasks such as adaptive ocean sampling. We describe a methodology for cooperative control of multiple vehicles based on virtual bodies and artificial potentials (VBAP). This methodology allows for adaptable formation control and can be used for missions such as gradient climbing and feature tracking in an uncertain environment. We discuss our implementation on a fleet of autonomous underwater gliders and present results from sea trials in Monterey Bay in August 2003. These at-sea demonstrations were performed as part of the Autonomous Ocean Sampling Network (AOSN) II project.

Potential-based obstacle avoidance in formation control

“…Therefore, V I adjusts the relative position among the agents, V o keeps the agents away from colliding with the obstacles. We will prove that the formation of the agents modeled by (1) is stable under control law (5), that is, all the agents can reach their destinations and during the process they can keep formation and avoid obstacles. From the traditional PID controller view, some explanations for control law (5) are also given here, including the proportional-derivative control.…”

“…Theorem 1 For a class of systems modeled as equation (1) and with the characteristics 1, 2, 3, the whole system is stable by using control law (5) to drive the agents to their destination while keeping formation and avoiding obstacles.…”

“…Formation control via a virtual leader based on potential fields can be found in [2,5]. Also, authors of [6] use the concept of artificial potential trenches to control the formation in the sense of queues.…”

Coordinating control of multiple rigid bodies based on motion primitives

“…Motivations for such research stem from the inherent strength and robustness in a coordinated group when dealing with tasks such as searching, surveying and mapping. For example, a fleet of underwater vehicles is used collectively for adaptive ocean sampling [1]. An important goal is to coordinate the motion of the vehicles so that the resolution of sensing array is optimized to minimize the estimation error in a sampled environment.…”

A mobile monitoring system to understand the processes controlling episodic events in Corpus Christi Bay

“…Instead of selecting the transect route, sampling frequency, and total number of measurements prior to the start of the monitoring study, it is now possible to implement adaptive/sequential plans that will guide the choice of sampling route where more information about the parameter of interest can be gathered (Thompson and Seber 1996). This adaptive sampling scheme has gained wider acceptance as a valuable tool for the sampling of the abundant but clustered population of data in natural sciences (Fiorelli et al 2006). In addition to the implementation of an adaptive sampling technique, the proper characterization of the spatial and temporal scale of the event depends on the type of platforms where in situ sensors are installed (e.g., mobile platforms, fixed platforms, bottom tripods, drifters, and floats; Dickey 1991; Dickey et al 1998).…”