Research on Automated Microassembly Technology for ICF Target Core Microdevices Based on Teleoperation

This letter presents a teleoperation-based solution to address the challenges of achieving high precision, flexibility, and efficiency in complex microdevice assembly. We developed an automated microassembly system that integrates a decision tree for predicting operator intention with a leader-follower mapping model to suppress physiological tremor. The system's performance was rigorously evaluated through demanding assembly experiments using Inertial Confinement Fusion (ICF) target core microdevices (half-hohlraums and target balls). Experimental results demonstrate effective operator intention recognition, with 80% accuracy for axial feed and 95% for pose adjustment. The system also achieved precise force and position control, limiting the maximum deformation of the gold hohlraum to 56μm and the maximum force on the target ball to 17.4μN. These findings validate the effectiveness and potential of this technical approach.

Authors

Institutions

Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2025-09-25
DOI
https://doi.org/10.1109/lra.2025.3614545
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Automated Microassembly Technology for ICF Target Core Microdevices Based on Teleoperation

Xin Yang, Hongwei Deng, Kejian Ni, Tao Chen et al.
IEEE Robotics and Automation Letters
Modular Robots and Swarm Intelligence
article

Research on Automated Microassembly Technology for ICF Target Core Microdevices Based on Teleoperation

Xin Yang, Hongwei Deng, Kejian Ni, Tao Chen, Hui Dai
article en

Abstract

This letter presents a teleoperation-based solution to address the challenges of achieving high precision, flexibility, and efficiency in complex microdevice assembly. We developed an automated microassembly system that integrates a decision tree for predicting operator intention with a leader-follower mapping model to suppress physiological tremor. The system's performance was rigorously evaluated through demanding assembly experiments using Inertial Confinement Fusion (ICF) target core microdevices (half-hohlraums and target balls). Experimental results demonstrate effective operator intention recognition, with 80% accuracy for axial feed and 95% for pose adjustment. The system also achieved precise force and position control, limiting the maximum deformation of the gold hohlraum to 56μm and the maximum force on the target ball to 17.4μN. These findings validate the effectiveness and potential of this technical approach.

IEEE Robotics and Automation LettersVol. 10(11)
Soochow University (CN)
Openalex Percentile: Top 73%
Modular Robots and Swarm Intelligence
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.