Abstract
This paper presents a strategy for chemical plume tracing (CPT) with soft obstacle avoidance, such as kelp forests or seaweed in near-shore, oceanic environments. The basic idea is to integrate a low-level fuzzy following obstacle behavior into a subsumption architecture for moth-inspired plume tracing. By on-line generation of dynamic reference targets (DRTs) on a course of the most recent CPT activity, an autonomous underwater vehicle (AUV) can quickly and correctly resume CPT maneuvering after passing obstacles. Simulation studies of CPT with obstacle avoidance are performed using a simulated plume with significant meander and filament intermittency in an environment with length scales of 100 m.
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