RABIT, a Robot Arm Bug Intervention Tool for Self-Driving Labs

Self-driving labs are transforming scientific research and accelerating experimentation using software-controlled lab equipment. These labs are exposed to human errors by inexperienced researchers working in the lab (e.g., setting incorrect target location could cause a robot arm to collide with an...

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Bibliographic Details
Main Authors: Wattoo, Zainab Saeed, Vitis, Petal, Zhu, Ruizhe, Depner, Noah, Zhang, Ivory, Hein, Jason, Gujarati, Arpan, Seltzer, Margo
Format: Conference Proceeding
Language:English
Subjects:
Chemistry
Computer bugs
Manipulators
Object recognition
Production
Robot sensing systems
rule-based anomaly detection
Safety
self-driving labs
Online Access:Request full text
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Summary:Self-driving labs are transforming scientific research and accelerating experimentation using software-controlled lab equipment. These labs are exposed to human errors by inexperienced researchers working in the lab (e.g., setting incorrect target location could cause a robot arm to collide with an expensive piece of equipment). We present RABIT, a Robot Arm Bug Intervention Tool, which (i) allows systematically specifying safety rules across diverse devices and (ii) evaluates and enforces these rules using simulation, a low-fidelity testbed, and a production environment. We report our experience adapting RABIT for the Hein Lab, a state-of-the-art research lab that blends advanced robotics with synthetic organic chemistry.
ISSN:2158-3927
DOI:10.1109/DSN58291.2024.00043