Effectiveness of insect-inspired chemical plume-tracking algorithms in a shifting wind field

Abstract

Tracking a plume of chemical back to its source is made difficult due to the complexity of plume structure caused by turbulence and shifts in the prevailing wind direction. Insects overcome this problem using forms of anemotaxis, which involve traveling upwind when an attractive chemical is perceived. In this study, two series of insect-inspired plume-tracking algorithms were implemented on a mobile robot and their performance compared under changing wind conditions in a wind tunnel. The robot was capable of sensing wind velocity and the level of a plume of ions. Ion sensors respond and recover far more rapidly than do conventional chemical sensors, so the substitution of an ion plume for a chemical plume allowed the algorithms to be implemented with rapid responses to changing plume concentration. The addition of a specific behavioral response to a wind shift decreased the time taken for the robot to find the plume source in the event of a wind shift. Increased speed came with only a minor drop in the success rate of the searching. Anemotaxis is an effective approach to chemical plume tracking with robots. The performance of these simple algorithms can be improved by modest increases in the complexity of the algorithms.