NSF Award
2335910
Laboratory automation increases precision and efficiency of science experiments. Advances in low-cost sensors, actuators, robotic systems, and control systems have lowered the barrier to entry to laboratory automation such that fully self-driving labs will have the potential to enable new practices of science experiment and to accelerate scientific exploration progress. There is a critical need to develop the principles and methodologies for self-driving laboratories. These systems will likely draw from best practices and experiences learned in data science, human-machine interaction, manufacturing and quality control, open-source ecosystems, and laboratory science methods. <br/><br/>The proposed workshop will convene leaders in self-driving laboratories and related areas including data science, robotics, manufacturing, and open-source ecosystems to define a roadmap for self-driving laboratories. Experts will discuss on latest advances and current challenges in automated sample preparation, experiment generation, data collection, and data analysis. The workshop will help identify major themes and assess on how future, interconnected goals can be best supported in a research context. By convening community leader around related topics, the workshop will seed cross-discipline collaboration on infrastructure that can support a broad range of sciences, which may include more complex experiments to accelerate scientific discovery and perform cost effective verification and validation.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
