Robotic Powder Grinding with a Soft Jig for Laboratory Automation in Material Science

Nakajima, Yusaku; Hamaya, Masashi; Suzuki, Y.; Hawai, Takafumi; Drigalski, Felix von; Tanaka, Kazutoshi; Ushiku, Yoshitaka; Ono, Kanta

doi:10.1109/iros47612.2022.9981081

Cited by 8 publications

(1 citation statement)

References 38 publications

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“…However, major challenges in perception and decision-making limit the robust deployment of general-purpose robotic systems for flexible lab automation. For this reason, many works in the literature address lab automation for specific tasks-for example, mechanical tasks such as retrieving samples of crystals by scraping the wall of a vial 47 and grinding powder with a soft jig 48 have been demonstrated. Pouring liquid using visual feedback 49 and weight feedback 50 have been studied as an alternative method of transferring liquid.…”

Section: General-purpose Robot Applied For Chemistrymentioning

confidence: 99%

Self-Driving Laboratories for Chemistry and Materials Science

Tom,

Schmid,

Baird

et al. 2024

Preprint

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Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with the autonomization of experiment planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review article provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research, and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

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Section: General-purpose Robot Applied For Chemistrymentioning

confidence: 99%

Self-Driving Laboratories for Chemistry and Materials Science

Tom,

Schmid,

Baird

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Self-Driving Laboratories for Chemistry and Materials Science

Tom,

Schmid,

Baird

et al. 2024

Chem. Rev.

View full text Add to dashboard Cite

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

show abstract