AI -Driven Autonomous Robotic Experiment System
for Achieving SDGs
AI -Driven Autonomous Robotic Experiment System
for Achieving SDGs
To dramatically improve the efficiency of research and development of new materials that are essential for achieving carbon neutrality, we are developing an autonomous system for materials research and development that utilizes AI and robots. Through unique technologies such as robotic powder handling, the system enables the autonomous completion of an entire series of material research processes, from material synthesis and sample preparation to material evaluation and analysis, all without human intervention, which includes sophisticated tasks and expert decision-making that were previously performed by skilled personnel.
- Affiliation:
- Osaka University
Graduate School of Engineering
Department of Applied Physics Ono Laboratory
- Representative:
- Kanta Ono
Professor,
Osaka University
Graduate School of Engineering
Department of Physics,
Course of Applied Physics,
Ono Laboratory
Ono Kanta PhD
Ph.D. in Science, The University of Tokyo. After working as an assistant professor at the Graduate School of Engineering, The University of Tokyo, and as an associate professor at the High Energy Accelerator Research Organization (KEK), he became a professor at the Department of Physics, Graduate School of Engineering, Osaka University.
SOCIALSocial Implementation
Significantly Enhancing the Efficiency of Measurement Evaluation and Analysis in Materials Research and Development
This system enables companies involved in materials research and development to perform measurement, evaluation, and analysis work, which is a heavy burden for them, with quality on par with or surpassing that of experts by utilizing robots and AI. The system aims to contribute to a significant increase in productivity in materials development at companies engaged in materials R&D, and to reduce the workload of skilled engineers, who are in short supply.
ORIGINALITYUniqueness, Passion for Development
Automating Tasks that Previously Relied on Skilled Experts by Integrating AI and Robot Technology
Autonomy in materials analysis is fully achieved only when the entire series of processes, including manual sample preparation, execution of optimal measurement experiments, analysis of measurement data, and interpretation of results, all of which require skilled workers, are automated. Until now, the execution of measurements has been automated, but sample preparation and interpretation of results have not been automated, as they rely on the skills and knowledge of experienced personnel. Our two unique technologies, (1) robotic powder handling technology and (2) AI-based measurement optimization, data analysis, and interpretation, have made this possible for the first time.
VISIONDream, Outlook, Business Image
Advancing R&D in the Fields of Next-Generation Batteries, Ceramics, Catalysts, and More
The social implementation of this system will significantly improve the work efficiency of companies involved in materials R&D, enabling materials researchers to focus on more creative research activities by providing more advanced and reproducible materials analysis that surpasses conventional methods. The system is expected to be used in the fields of next-generation battery R&D, ceramics, catalysts, and more, and is anticipated to contribute to solving global issues such as carbon neutrality and SDGs by improving the efficiency and productivity of an increasing number of R&D sites.
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