TY - GEN
T1 - A framework for industrial robot training in cloud manufacturing with deep reinforcement learning
AU - Liu, Yongkui
AU - Yao, Junying
AU - Lin, Tingyu
AU - Xu, He
AU - Shi, Feng
AU - Xiao, Yingying
AU - Zhang, Lin
AU - Wang, Lihui
N1 - Publisher Copyright:
Copyright © 2020 ASME
PY - 2020
Y1 - 2020
N2 - Cloud manufacturing is a service-oriented networked manufacturing model that embraces the concept of 'Everything-as-a-Service'. In cloud manufacturing, distributed manufacturing resources encompassed in the product lifecycle are transformed into manufacturing services. Industrial robots are an important category of manufacturing resources in cloud manufacturing. During the past years, robots have been demonstrated to be able to learn various dexterous manipulation skills through training with deep reinforcement learning (DRL). In cloud manufacturing, there are many complex industrial application scenarios that require dexterous robots. Hence, robot training, which enables robots to learn various manipulation skills, becomes an important requirement for cloud manufacturing in the future, leading to the concept of 'Robot Training-as-a-Service'. This paper focuses on industrial robot training in the context of cloud manufacturing. First, related work on cloud manufacturing, DRL, DRL-based robot training, and cloud-edge collaboration is briefly reviewed and analyzed. Then, a framework for industrial robot training in cloud manufacturing with DRL is proposed, and a simplified case study is presented to demonstrate the basic principle of the framework. Finally, possible future research issues are discussed.
AB - Cloud manufacturing is a service-oriented networked manufacturing model that embraces the concept of 'Everything-as-a-Service'. In cloud manufacturing, distributed manufacturing resources encompassed in the product lifecycle are transformed into manufacturing services. Industrial robots are an important category of manufacturing resources in cloud manufacturing. During the past years, robots have been demonstrated to be able to learn various dexterous manipulation skills through training with deep reinforcement learning (DRL). In cloud manufacturing, there are many complex industrial application scenarios that require dexterous robots. Hence, robot training, which enables robots to learn various manipulation skills, becomes an important requirement for cloud manufacturing in the future, leading to the concept of 'Robot Training-as-a-Service'. This paper focuses on industrial robot training in the context of cloud manufacturing. First, related work on cloud manufacturing, DRL, DRL-based robot training, and cloud-edge collaboration is briefly reviewed and analyzed. Then, a framework for industrial robot training in cloud manufacturing with DRL is proposed, and a simplified case study is presented to demonstrate the basic principle of the framework. Finally, possible future research issues are discussed.
KW - Cloud manufacturing
KW - Deep reinforcement learning
KW - Industrial robot training
KW - Transfer learning
UR - https://www.scopus.com/pages/publications/85101429070
U2 - 10.1115/MSEC2020-8355
DO - 10.1115/MSEC2020-8355
M3 - 会议稿件
AN - SCOPUS:85101429070
T3 - ASME 2020 15th International Manufacturing Science and Engineering Conference, MSEC 2020
BT - Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability
PB - American Society of Mechanical Engineers
T2 - ASME 2020 15th International Manufacturing Science and Engineering Conference, MSEC 2020
Y2 - 3 September 2020
ER -