Robotic Intelligent Assembly
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Beschreibung
This book explores peg-in-hole assembly strategies to study robotic intelligent assembly. It presents several state-of-the-art principles for peg-in-hole assembly strategies, supported by experimental evidence. In pursuit of theoretical innovation, the author summarizes their research on robotic intelligent assembly over the past decade, highlighting the limitations of model-based algorithms in complex assembly environments and the importance of data efficiency for learning-based algorithms. Each algorithm is supported by extensive experimentation and results demonstrating its effectiveness. A review of research ideas provides readers with a comprehensive understanding of the progress made in this field. This monograph is intended for undergraduate and postgraduate students interested in robotic intelligent assembly, researchers studying robotic intelligent assembly algorithms, and electronic, mechanical, and computer engineers engaged in industrial robot-assisted assembly.
This book explores peg-in-hole assembly strategies to study robotic intelligent assembly. It presents several state-of-the-art principles for peg-in-hole assembly strategies, supported by experimental evidence. In pursuit of theoretical innovation, the author summarizes their research on robotic intelligent assembly over the past decade, highlighting the limitations of model-based algorithms in complex assembly environments and the importance of data efficiency for learning-based algorithms. Each algorithm is supported by extensive experimentation and results demonstrating its effectiveness. A review of research ideas provides readers with a comprehensive understanding of the progress made in this field. This monograph is intended for undergraduate and postgraduate students interested in robotic intelligent assembly, researchers studying robotic intelligent assembly algorithms, and electronic, mechanical, and computer engineers engaged in industrial robot-assisted assembly.
Introduces several state-of-the-art robotic peg-in-hole assembly strategies Provides sufficient experimental data and charts to facilitate reader’s understanding Offers valuable guidance for the design and further innovation of peg-in-hole assembly strategies
Autor*in
Jing Xu
Themen in »Robotic Intelligent Assembly«
Peg-in-hole Assembly Learning from Demonstrations Assembly Trajectory Generation Model-based Strategies Deep-Deterministic Policy Gradient(DDPG) Learning from Environments Robotic Assembly