Research

Research Topics

The lab undertakes research in a broad range of disciplines, aiming to integrate multiple subjects of studies with advanced machine learning methods. Currently, the lab is focusing on the following projects.

1. Odour Sensing

Olfactory information is an important ability for living creatures. Animals can utilise it to localise foods, water and mates. However, the slow reaction speed of conventional gas sensors is a critical issue for an odour tracking robot. The electroantennogram (EAG) is a technique that can extract neural signals from an antenna of an insect for detecting odour plumes. However, due to its small amplitude, the EAG signal can be easily influenced by the surroundings. To obtain accurate detection results, special algorithms were developed to filter the signal recorded in noisy environments. This technique can hence be applied to flying robots for odour tracking later.

Keywords: odour sensing, electroantennogram, insect antenna

2. Analysis of Insect Flight

Understanding the causal impacts among various parameters is essential for designing micro aerial vehicles (MAVs). Computational fluid dynamics (CFD) simulation enables us to analyse and compare the flow fields under different flying patterns. However, it regularly takes considerable computational time for obtaining precise results. To increase the analysis process, machine learning methods were introduced to shorten the computational time. Moreover, the technique of optimisation algorithm was implemented so that an effective flight pattern could be concluded without performing thousands of simulations.

Keywords: insect flight, flapping wing, machine learning