Intelligent Experiment Robotic Systems Design for Material Preparation and Detection

This article presents an intelligent robotic system developed for experiments in the materials science laboratory, specifically focusing on coating preparation via layer-by-layer self-assembly techniques and hydrophobic detection. The system integrates two collaborative robotic arms, enhanced with dynamic movement primitives (DMPs), to mimic human manipulation skills and bolster the robots’ imitation capabilities. Additionally, a mobile robotic arm facilitates autonomous operations. A key component is an independently designed optical detection device capable of measuring water droplet angles. Coupled with a compatible simulation platform, the system can perform virtual experiments and generate trajectories for obstacle avoidance, and in which generative adversarial imitation learning (GAIL) in simulating robot trajectories. This article details the system’s construction, process design encompassing the robotic systems, optical detection device, simulation, and visualization platform. It also explores the vast potential of future AI-driven laboratories in materials science, biology, medicine, and chemistry.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Systems Man and Cybernetics Systems
Published
2024-12-11
DOI
https://doi.org/10.1109/tsmc.2024.3501318
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligent Experiment Robotic Systems Design for Material Preparation and Detection

Xinbo Yu, Wei He, Yingru Sun, Dawei Zhang et al.
IEEE Transactions on Systems Man and Cybernetics Systems
Manufacturing Process and Optimization
article

Intelligent Experiment Robotic Systems Design for Material Preparation and Detection

Xinbo Yu, Wei He, Yingru Sun, Dawei Zhang, Wu Yifan
article en

Abstract

This article presents an intelligent robotic system developed for experiments in the materials science laboratory, specifically focusing on coating preparation via layer-by-layer self-assembly techniques and hydrophobic detection. The system integrates two collaborative robotic arms, enhanced with dynamic movement primitives (DMPs), to mimic human manipulation skills and bolster the robots’ imitation capabilities. Additionally, a mobile robotic arm facilitates autonomous operations. A key component is an independently designed optical detection device capable of measuring water droplet angles. Coupled with a compatible simulation platform, the system can perform virtual experiments and generate trajectories for obstacle avoidance, and in which generative adversarial imitation learning (GAIL) in simulating robot trajectories. This article details the system’s construction, process design encompassing the robotic systems, optical detection device, simulation, and visualization platform. It also explores the vast potential of future AI-driven laboratories in materials science, biology, medicine, and chemistry.

IEEE Transactions on Systems Man and Cybernetics SystemsVol. 55(2)
University of Science and Technology Beijing (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 68%
Manufacturing Process and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.