LAUSR

In this study, we designed and experimentally verified the placement of odor sensors and an algorithm using the aero-olfactory effect of a palm-sized quadcopter to solve the 3-D chemical plume tracking (3-D-CPT) problem. Solving 3-D-CPT is important in engineering as it helps perform rescue operations during disasters and identify sources of harmful substances. Moreover, the odor sensors must be properly located and a CPT algorithm be applied to improve the tracking performance of a chemical. However, studies regarding the use of quadcopters for solving the 3-D-CPT problem are scarce, and the relationship between the odor sensor location and algorithm is debatable. Hence, we utilized particle image velocimetry (PIV), an airflow visualization technology, to evaluate the arrival direction of chemicals at different heights. The results showed that odor sensors must be placed on the upper and front surfaces of a quadcopter to monitor the chemicals three-dimensionally. Additionally, we designed a 3-D surge-casting algorithm, which is an extension of the CPT strategy of a flying moth, that is, surge casting, to accommodate the proposed odor sensor placement. By conducting 3-D-CPT experiments based on different heights of odor sources using the proposed system, we discovered that even in an environment with significant changes in the wind direction the CPT performance is better than that of the conventional 3-D-CPT algorithm. Thus, 3-D-CPT should be further improved to enable its application in unknown and cluttered environments. In this study, we improved the 3-D-CPT performance of a palm-sized quadcopter by designing an appropriate sensor arrangement and algorithm balance.