Project will start in Sept 2024!

Project members: Kefeng Huang, Jonathon Pipe, Dr.ir. Jihong Zhu, Prof. Andy Tyrrell and Prof. Ian Fairlamb.

Chemistry experimentation is fundamental to scientific research and development. Nevertheless, it often entails time-consuming, labour-intensive processes that are susceptible to human error. Robotic systems hold immense promise in transforming this field by automating and streamlining chemistry laboratory experiments. However, due to the intricate dexterity required, programming the behaviour through explicit instructions can be a formidable challenge.

This research endeavour seeks to tap into human expertise and explore the potential of utilising Learning from Demonstrations (LfD) techniques. This approach empowers robots to learn directly from human demonstrations, enabling them to perform chemistry experiments with increased efficiency and precision. The study will specifically investigate the application of Schlenk line techniques, transferring knowledge and extensive hands-on experience from humans to robot through kinesthetic teaching or teleoperation.