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Jakub Glowacki

dblp:319/4915 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › task automation
laboratory automation
0.612022
ARChemist: Autonomous Robotic Chemistry System Architecture · ICRA 2022
Robotics › Robot manipulation
task automation
0.612022
ARChemist: Autonomous Robotic Chemistry System Architecture · ICRA 2022

Methods — techniques the papers use, named apart from their topics

system architecture design · 0.6
YearPublicationVenuePosition
2022 ARChemist: Autonomous Robotic Chemistry System Architecture
abstract
Automated laboratory experiments have the potential to propel new discoveries, while increasing reproducibility and improving scientists' safety when handling dangerous materials. However, many automated laboratory workflows have not fully leveraged the remarkable advancements in robotics and digital lab equipment. As a result, most robotic systems used in the labs are programmed specifically for a single experiment, often relying on proprietary architectures or using unconventional hardware. In this work, we tackle this problem by proposing a novel robotic system architecture specifically designed with and for chemists, which allows the scientist to easily reconfigure their setup for new experiments. Specifically, the system's strength is its ability to combine together heterogeneous robotic platforms with standard laboratory equipment to create different experimental setups. Finally, we show how the architecture can be used for specific laboratory experiments through case studies such as solubility screening and crystallisation.
Hatem Fakhruldeen, Gabriella Pizzuto, Jakub Glowacki, Andrew I. Cooper
ICRA3