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Collaborating multi-agent systems can handle complex tasks with several or changing mission objectives. We developed a potential field method that allows various information layers to influence the control over a group of vehicles. The gradient of the potential field is the driving force for local action, whereas the global waypoint is determined by the minimum of the agent's potential field. The driving force to the global waypoint is a virtual spring-mass-damper system that pulls the agent towards its waypoint, restricted by the local gradient of the agent's potential field.

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In marine environments, sparse in-situ measurements can be used for the estimation of the fluid dynamic field. To make best use of a mobile sensor network in an environment whose dynamics can be described by the Navier-Stokes equations, we developed a framework for data assimilation with motion-constrained underwater vehicles, that takes the physical field properties into account while sampling. Our algorithm uses an ensemble Kalman filter that propagates hundreds of slightly varied coarse fluid dynamic simulations through time. Flow and scalar measurements from the mobile sensors are integrated into all ensemble members. We implemented a model predictive controller to calculate covariance minimizing paths from the estimated flow field and motion primitives of the vehicles, which are affected by a strong current. Thereby, we were able to indirectly track dynamically changing wall temperatures through measurements of flow field variables.

A hyperbolic acoustic system for underwater robot self-localization is presented. Anchored transducers send acoustic signals which are observed by a receiver. The system is passive with one-way signal transmission. Time differences of arrival (TDOAs) between the emitted signals are estimated by the receiver via cross-correlation. These TDOAs are fed to an Extended Kalman Filter to estimate the global position of the receiver. We describe the complete signal processing chain as well as challenges in hardware and software design. Experimental results in air and water show the feasibility of the system. This paper demonstrates that acoustic oneway localization is possible with off-the-shelf hardware in experimental test tanks.