ARM Lunch, Learn, Engage | Generalizable Robotics in Lab Automation

Featuring Animesh Garg, Georgia Tech College of Computing

Professor Animesh Garg (COC) will lead a discussion around how the advent of language- and image-based foundation models promises to solve long standing challenges in robotics such as general-purpose perception and reasoning. This new capability has accelerated the autonomy of robotics, and as a result these systems are increasingly viable for flexible automation in scientific labs. We will present a framework for robot planning with visual feedback in the loop to solve open world reasoning. Further, we will present an integrated system, ORGANA, for interactive chemistry lab automation. 


Autonomous Research for Materials (ARM) is an Institute for Materials (IMat) Strategic Initiative seeking to connect and engage researchers in materials science, data sciences, and robotics to form partnerships that advance autonomous experimentation and self-driving laboratories. Inquiries about the ARM initiative should be directed to Mark Losego at