Garment production is a laborious process that relies primarily on manual operations. Smart robots are set to play a vital role in future automations and assist human workers with repetitive and/or high-risk tasks. To achieve interactive human-robot collaborations, robots need to learn and understand how humans work and thus a cost-effective means of digitising manual operations is of the essence. In this project, we aim at developing an innovative approach to high-fidelity, real-time full-body motion capture for garment workers without using specialty cameras.
A lot of diseases can be transmitted via airborne agents, such as viruses spreading through droplets. The concentrations of these airborne agents are usually too low in the environment and it has created difficulties for the current detection instruments available in the market. We aim to fill this gap by developing new technologies to enhance detection and diagnostics of airborne viruses.