Marine Adaptive Sampling Scheme Design for Mobile Platforms under Different Scenarios

Abstract

Marine adaptive sampling is a technique that makes full use of limited observation resources by selecting the optimal positions. Recently, the design of an adaptive sampling scheme based on a mobile platform has become a research hotspot. However, adaptive sampling system involves multiple subsystems, and the attributes as well as tasks are always different, which may lead to different sampling scenarios. A great deal of research has been conducted for specific situations, especially with fixed starting and ending points. However, systematic design and simulation experiments under various circumstances are still lacking. How to design the adaptive observation system, so as to cope with the observation task under different scenarios, is still a problem worth studying. Aiming to solve this problem, we designed a systematic scheme design process. The process includes setting up and verifying the background field, adopting the hierarchical optimization framework to adapt to different circumstances, and variable adjustments for twin frames. The needs covered in this paper include not having a fixed starting point and ending point, only having a fixed starting point, having a fixed starting point and ending point, increasing sampling coverage, and simple obstacle avoidance. Finally, the relevant conclusions are applied to the multi-platform simultaneous observation scenario. It provides a systematic flow pattern for designing adaptive sampling scheme of mobile platforms.