most citedAccelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges from the 2024 IEEE ICRA Workshop, Yokohama, Japan

2 citations · 4 across the 5 of their papers we have counts for

collaborators

6 papers

cs.RO2025

PREVENT: Proactive Risk Evaluation and Vigilant Execution of Tasks for Mobile Robotic Chemists using Multi-Modal Behavior Trees

Satheeshkumar Veeramani, Zhengxue Zhou, Francisco Munguia-Galeano +5

Mobile robotic chemists are a fast growing trend in the field of chemistry and materials research. However, so far these mobile robots lack workflow awareness skills. This poses th…

cs.RO20252 cited

Chemist Eye: A Visual Language Model-Powered System for Safety Monitoring and Robot Decision-Making in Self-Driving Laboratories

Francisco Munguia-Galeano, Zhengxue Zhou, Satheeshkumar Veeramani +4

The integration of robotics and automation into self-driving laboratories (SDLs) can introduce additional safety complexities, in addition to those that already apply to convention…

cs.RO2025

Multimodal Behaviour Trees for Robotic Laboratory Task Automation

Hatem Fakhruldeen, Arvind Raveendran Nambiar, Satheeshkumar Veeramani +4

Laboratory robotics offer the capability to conduct experiments with a high degree of precision and reproducibility, with the potential to transform scientific research. Trivial an…

cs.RO2025

FLIP: Flowability-Informed Powder Weighing

Nikola Radulov, Alex Wright, Thomas Little +2

Autonomous manipulation of powders remains a significant challenge for robotic automation in scientific laboratories. The inherent variability and complex physical interactions of…

cs.RO2025

An Open-source Capping Machine Suitable for Confined Spaces

Francisco Munguia-Galeano, Louis Longley, Satheeshkumar Veeramani +4

In the context of self-driving laboratories (SDLs), ensuring automated and error-free capping is crucial, as it is a ubiquitous step in sample preparation. Automated capping in SDL…

cs.RO20252 cited

Accelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges from the 2024 IEEE ICRA Workshop, Yokohama, Japan

Andrew I. Cooper, Patrick Courtney, Kourosh Darvish +20

Science laboratory automation enables accelerated discovery in life sciences and materials. However, it requires interdisciplinary collaboration to address challenges such as robus…