Feedback Control and Adaptive Learning in Optical-Tweezer Robotics - Li, Xiang; Miao, Shu; Cheah, Chien Chern
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Feedback Control and Adaptive Learning in Optical-Tweezer Robotics is a comprehensive guide to merging robotic feedback control with optical trapping techniques in cell manipulation. It begins by providing foundational knowledge in dynamic modeling and control theory, essential for understanding optical-tweezer robotics' complexities. The book explores optical trapping principles, discussing traditional approaches' constraints and challenges. It then introduces a unified control methodology designed for dynamic adaptation to cell movement and escape scenarios, highlighting the importance of…mehr

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Produktbeschreibung
Feedback Control and Adaptive Learning in Optical-Tweezer Robotics is a comprehensive guide to merging robotic feedback control with optical trapping techniques in cell manipulation. It begins by providing foundational knowledge in dynamic modeling and control theory, essential for understanding optical-tweezer robotics' complexities. The book explores optical trapping principles, discussing traditional approaches' constraints and challenges. It then introduces a unified control methodology designed for dynamic adaptation to cell movement and escape scenarios, highlighting the importance of closed-loop control strategies in navigating the interaction between optical forces and robotic manipulation. Additionally, the book delves into adaptive learning algorithms for real-time adjustments in unknown trapping stiffness, addressing challenges like limited field of view, stochastic disturbances, and handling multiple cells. It integrates open-access simulations and real-world experiments to reinforce theoretical concepts, offering practical examples. This unified approach's potential impact on biomedicine, biotechnology, and microscale robotics is emphasized, making it an invaluable resource for readers in these fields.
Autorenporträt
Xiang LI is an Associate Professor with the Department of Automation, Tsinghua University. He has been the Associate Editor of IEEE Robotics and Automation Letters since 2022 and the Associate Editor of IEEE Transactions on Automation Science and Engineering since 2023. He was the Associate Editor of IEEE Robotics & Automation Magazine from 2019 to 2021 and the Associate Editor of ICRA in 2019, 2020, 2021, and 2023. He received the Highly Commended Paper Award in 2013 IFToMM, the Best Paper in Robotic Control in 2017 ICAR, the Best Application Paper Finalists in 2017 IROS, the T. J. Tarn Best Paper in Robotics in 2018 IEEE ROBIO, and the Best Paper Award in 2023 ICRA DOM Workshop. He is the Program Chair of the 2023 IEEE International Conference on Real-time Computing and Robotics. He is a Senior Member of IEEE.