A full-scale adaptive ocean sampling network was deployed throughout the month-long 2006 Adaptive Sampling and Prediction (ASAP) field experiment in Monterey Bay, California. One of the central goals of the field experiment was to test and demonstrate newly developed techniques for coordinated motion control of autonomous vehicles carrying environmental sensors to efficiently sample the ocean. ...

Effective study of ocean processes requires sampling over the duration of long (weeks to months) oscillation patterns. Such sampling requires persistent, autonomous underwater vehicles that have a similarly, long deployment duration. The spatiotemporal dynamics of the ocean environment, coupled with limited communication capabilities, make navigation and localization difficult, especially in co...

Underwater gliders (UGs) are becoming popular in ocean exploration. However, the main limitation for their development is supply of energy. This paper proposes a novel energy harvesting mechanism an underwater glider equipped with thermal buoyancy engine. The engine changes glider, due to difference temperature ocean, and it drives up down water. These manoeuvres drive turbine behind harvest Ba...

Underwater gliders are prevailing in oceanic observation nowadays for their flexible deployment and low cost. However, the limited onboard energy constrains application, hence motion pattern optimization analysis key to maximizing range of glider while maintaining acceptable navigation preciseness glider. In this work, a Multi-Objective Artificial Bee Colony (MOABC) algorithm is used solve cons...