A Learning-Based Assembly Sequence Planning Method Using Neural Combinatorial Optimization With Satisfactory Generalization Ability

This paper proposes a specific and effective real-time sequence planning method using robot manipulators to complete complex assembly tasks. Many previous studies developed different traversal methods to obtain the optimal assembly sequence. Besides, a number of algorithms were proposed to enhance f...

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Vydané v:	IEEE transactions on automation science and engineering Ročník 22; s. 8952 - 8964
Hlavní autori:	Hou, Ruiming, Xu, Sheng, Yang, Chenguang, Duan, Jianghua, Wu, Xinyu, Xu, Tiantian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.01.2025
Predmet:	Assembly Assembly sequence planning (ASP) contact matrix Cost function Costs Manipulators neural combinatorial optimization (NCO) Optimization Planning pointer network Production reinforcement learning (RL) Robot kinematics Robots Stability analysis
ISSN:	1545-5955, 1558-3783
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