Incorporating a time history of ambient wind improves odor plume tracking success in simulated flying agents

Insects exhibit exceptionally robust algorithms for navigating airborne turbulent odor plumes while searching for food or mates. There is growing interest in replicating their success with artificial agents. Prior experiments with flying insects in laminar wind tunnels suggest they rely on a “surge and cast” behavior, where the animals turn upwind after encountering the plume, and zigzag in the crosswind direction after losing track of the odor. Despite myriad engineering efforts, the success rate of biological agents remains unmatched, especially under conditions with rapid changes in wind direction. Here, we suggest that an artificial agent can significantly improve its source estimation success rate if it incorporates a memory of wind direction. In our study, we gave our agents a memory of wind direction which it uses along with “surge and cast” to generate a collection of finite candidate routes. With subsequent odor encounters and optimizations, the agent estimates which of these paths is most likely to lead to the actual source. We compared our agent’s performance with the “surge and cast” algorithm and our results suggest that incorporating a time history of wind can substantially improve plume tracking in artificial agents and may also be employed by flying insects.