2 citations · 2 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
Learning to bag with a simulation-free reinforcement learning framework for robots
Francisco Munguia-Galeano, Jihong Zhu, Juan David Hernández +1
Bagging is an essential skill that humans perform in their daily activities. However, deformable objects, such as bags, are complex for robots to manipulate. This paper presents an…
Deep Reinforcement Learning with Explicit Context Representation
Francisco Munguia-Galeano, Ah-Hwee Tan, Ze Ji
Reinforcement learning (RL) has shown an outstanding capability for solving complex computational problems. However, most RL algorithms lack an explicit method that would allow lea…