AUTHOR=Jin Piaopiao , Lin Yinjie , Song Yaoxian , Li Tiefeng , Yang Wei 

TITLE=Vision-force-fused curriculum learning for robotic contact-rich assembly tasks

JOURNAL=Frontiers in Neurorobotics

VOLUME=17

YEAR=2023

URL=https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2023.1280773

DOI=10.3389/fnbot.2023.1280773

ISSN=1662-5218

ABSTRACT=<p>Contact-rich robotic manipulation tasks such as assembly are widely studied due to their close relevance with social and manufacturing industries. Although the task is highly related to vision and force, current methods lack a unified mechanism to effectively fuse the two sensors. We consider coordinating multimodality from perception to control and propose a vision-force curriculum policy learning scheme to effectively fuse the features and generate policy. Experiments in simulations indicate the priorities of our method, which could insert pegs with 0.1 mm clearance. Furthermore, the system is generalizable to various initial configurations and unseen shapes, and it can be robustly transferred from simulation to reality without fine-tuning, showing the effectiveness and generalization of our proposed method. The experiment videos and code will be available at <ext-link ext-link-type="uri" xlink:href="https://sites.google.com/view/vf-assembly" xmlns:xlink="http://www.w3.org/1999/xlink">https://sites.google.com/view/vf-assembly</ext-link>.</p>