A Framework to Evolutionary Path Planning for Autonomous Underwater Glider
In recent decade years, AUG has been attached importance to oceanographic sampling tool. AUG is a buoyancy driven vehicle with low energy consumption, and capable of long-term and large-scale oceanographic sampling. However, ocean environment is characterized by variable and severe current fields, which jeopardizes AUG cruise. Therefore, an efficient path planning is a key point that can assist AUG to arrive at each waypoint and reduces the energy consumption to prolong AUG sampling time. To improve AUG cruise efficiency, a path planning framework with evolutionary computation is proposed to map out an optimal cruising path and increases AUG mission reachability in this work.
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