Bioinspired algorithm for autonomous sensor-driven guidance in turbulent chemical plumes

We designed and implemented a control algorithm for sensor-mediated chemical plume tracking in a turbulent flow environment. In our design, we focused on development of a signal processing strategy capable of replicating behavioral responses of actively tracking blue crabs (Callinectes sapidus) to chemical stimuli. The control algorithm is evaluated in a hardware platform that allows motion in two directions (i.e. forward-back and left-right). The geometric arrangement of the sensor array is inspired by the location of blue crab sensor populations. Upstream motion is induced by a binary response to supra-threshold spikes of concentration, and cross-stream steering is controlled by contrast between bilaterally-separated sensors. Like animal strategies, the developed control algorithm is dynamic. This property allows the algorithm to function effectively in the highly irregular turbulent environment and produces adaptive adjustments of motion to minimize the distance to the source of a plume. Tracking trials indicate that roughly 80% of the tracks successfully stop near the plume source location. Both success rate and movement patterns of the tracker compare favorably to that of blue crabs searching for odorant plume sources, thus suggesting that our sensory-mediated behavior hypothesis are generally accurate and that the associated tracking mechanisms may be successfully implemented in hardware.