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Multi-domain autonomous sensor networks are essential for reducing capability gaps between different kinds of sensing platforms. Design of an efficient network can provide seamless sensing capability. Furthermore, to achieve operational persistency, nodes of the networks are required to be robust and affordable. Field robotics has other challenges in addition to robustness and in particular the logistics...
Adaptive sampling algorithms and behavior-based approaches can aid in the rapid and accurate in-situ measurement and characterization of coastal environmental features such as industrial thermal effluent jets and plumes. To enable the development of these techniques we present a collection of simulation, estimation, and field tools for use within the Mission Oriented Operations Suite (MOOS). Key features...
This paper presents our latest results in the development of biomimetic batoid robots. Our goal is to utilize these robots for autonomous environmental exploration and monitoring missions in coastal environments. These new robots will be part of a larger heterogeneous robotic network already being developed by our group which combines traditional robotic vehicles with biomimetic ones to leverage advantages...
This paper examines the detection of landmarks in the presence of false measurements from a blazed array sonar using random finite set models. A clutter rejection filter that is based on the fusion of the moment-approximation of the posterior density, also known as probability hypothesis density (PHD), within the random finite set framework with the conventional Extended Kalman Filter simultaneous...
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