Reinforcement learning-based simulation and automation for tower crane 3D lift planning

Tower crane lift planning is important to timely provide resources to workplaces. However, previous planning approaches are still impractical because the lifting time of a plan is barely considered and the lifting path is frequently non-executable by operators. This paper describes a reinforcement l...

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Veröffentlicht in:	Automation in construction Jg. 144; S. 104620
Hauptverfasser:	Cho, SungHwan, Han, SangUk
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.12.2022
Schlagworte:	3D dynamic simulation Motion planning Path planning Reinforcement learning algorithms: on-policy and off-policy Reward function Tower crane Tower crane Motion planning 3D dynamic simulation Path planning Reward function Reinforcement learning algorithms: on-policy and off-policy
ISSN:	0926-5805, 1872-7891
Online-Zugang:	Volltext
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