This benchmark-ready simulation framework could be useful for the biology-oriented, as well as engineering-oriented studies, assisting in deducing the evolutionary efficient strategies and improving self-propelled autonomous systems in complex environments. The performance of the navigators was comprehensively analyzed using bio-statistical tests. We tested the performance of moth-like navigators of these models through various wind and odor spread parameters in a virtual turbulent environment. To demonstrate the applicability of our simulated framework as a benchmarking tool, we implemented two different moth-inspired navigation strategies for each strategy, specific modifications in the navigation module were carried out, resulting in four different navigation models. This work aims at closing this gap, using an open source, freely accessible simulation framework. However, comparing among various bio-inspired strategies is challenging, due to the lack of a componential framework that allows statistical comparison of their performances, in a controlled environment. Many studies have developed moths-inspired algorithms based on proposed strategies of odor-sourcing. Known for their expertise in locating an odor source, male moths feature a bio-inspirational model of olfactory navigation using chemosensory. Olfactory navigation is defined as a task of a self-propelled navigator with some sensors capabilities to detect odor (or scalar concentration) convected and diffused in a windy environment.
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