Safety-constrained Deep Reinforcement Learning control for human–robot collaboration in construction DOI
Kangkang Duan, Zhengbo Zou

Automation in Construction, Год журнала: 2025, Номер 174, С. 106130 - 106130

Опубликована: Март 23, 2025

Язык: Английский

Autonomous construction framework for crane control with enhanced soft actor–critic algorithm and real‐time progress monitoring DOI Creative Commons
Yao Xiao, Taiping Yang, Fan Xie

и другие.

Computer-Aided Civil and Infrastructure Engineering, Год журнала: 2025, Номер unknown

Опубликована: Янв. 30, 2025

Abstract With the shortage of skilled labors, there is an increasing demand for automation in construction industry. This study presents autonomous framework crane control with enhanced soft actor–critic (SAC‐E) algorithm and real‐time progress monitoring. SAC‐E a novel reinforcement learning superior speed training stability lifting path planning. In addition, robotic kinematics are implemented to ensure that can autonomously execute path. Last, hardware communication interfaces between robot operating system building information modeling (BIM) developed The performance proposed was demonstrated using robotized mobile stack concrete retaining blocks. results show be effectively used block update BIM platform.

Язык: Английский

Процитировано

1

Safety-constrained Deep Reinforcement Learning control for human–robot collaboration in construction DOI
Kangkang Duan, Zhengbo Zou

Automation in Construction, Год журнала: 2025, Номер 174, С. 106130 - 106130

Опубликована: Март 23, 2025

Язык: Английский

Процитировано

0