High-Accuracy Injection Using a Mobile Manipulation Robot for Chemistry Lab Automation

Abstract

Lab automation has the potential to accelerate scientific progress in the natural sciences, allowing tedious experiments that would require many hours of human time to be automated, enabling higher accuracy, efficiency, and repeatability. Mobile manipulation robots have the potential to work in chemistry labs designed for humans to complete tasks for which setting up customized factory-scale automation is premature or infeasible. We present a new method to enable a mobile manipulation robot to automate injections, a common task in chemistry labs when using equipment such as gas chromatographs (GCs) for analyzing the contents of a sample mixture. This task is challenging for a mobile manipulation robot due to the need to navigate to the equipment in the lab and then achieve millimeter-scale accuracy required for the syringe positioning. Our approach leverages deep learning to create a model capable of localizing the syringe with high accuracy using cameras mounted on the chemistry equipment, and then uses a visual servoing approach based on the syringe's needle localization to achieve the injection. We demonstrate that our approach is robust to uncertainty in navigation as well as uncertainty in the grasping position and orientation of the syringe, achieving errors sufficiently small to enable the mobile manipulation robot to automate injections in real chemistry equipment.