Motivated by the desire to optimally control the friction-induced stick-slip locomotion and sufficiently improve the energy efficacy, a novel trajectory synthesis and optimization scheme is proposed in this paper for a underactuated microrobotic system with dynamic constraints and couplings. The nonlinear microrobotic model utilizes combined tangential-wise and normal-wise vibrations for underactuated locomotion, which features a generic significance for the studies on microrobotic systems. Specifically, an analytical two-stage velocity trajectory is constructed under control indexes and physical constraints. Subsequently, the dynamic coupling behavior and the qualitative variation laws are characterized through rigorous bifurcation analysis. The synthesized trajectory is optimized and tuned via rigorous analysis based on the robot dynamics. The proposed trajectory planning mechanism provides a promising approach in determining the optimal viscoelastic parameters and trajectory parameters such that the optimal locomotion indexes can be met. Simulation results are presented to demonstrate the efficacy and feasibility of the proposed scheme.
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Recommended by Editor Hamid Reza Karimi. This work was partially supported by European Commission Marie Skłodowska-Curie SMOOTH (Smart robots for fire-fighting) project (H2020-MSCA-RISE-2016-734875) - https://doi.org/fusion-edu.eu/SMOOTH/, Royal Society International Exchanges Scheme (Adaptive Learning Control of a Cardiovascular Robot using Expert Surgeon Techniques) project (IE151224), and European Commission International Research Staff Exchange Scheme (IRSES) RABOT project (PIRSES-GA-2012-318902) - https://doi.org/rabot.fusion-edu.eu/.
Pengcheng Liu received the B.Sc. degree in electrical and electronic engineering and the M.Sc. degree in control theory and control engineering from Zhongyuan University of Technology, Zhengzhou, China, in 2007 and 2012, respectively, and the Ph.D. degree in robotics and control from Bournemouth University, Poole, United Kingdom, in 2017. He is currently a Research Fellow with the Lincoln Centre for Autonomous Systems (L-CAS), University of Lincoln, Lincoln, United Kingdom. His current research interests include nonlinear dynamics and control, computational intelligence, bio-inspired control, optimization, trajectory planning, and their applications to robotics.
Hongnian Yu received the B.Eng. degree in electrical and electronic engineering from Harbin Institute of Technology, Harbin, China, the M.Sc. degree in control engineering from Northeast Heavy Machinery Institute, Heilongjiang, China, and the Ph.D. degree in Robotics from King’s College London, United Kingdom. He is currently a Professor of computer science. His research interests include robotics, wireless networked control systems, RFID and its applications, mobile computing, modeling, scheduling, planning, and simulations of large discrete event dynamic systems with applications to manufacturing systems, supply chains, transportation networks and computer networks.
Shuang Cang received the B.Sc. (first class Hons.) degree in mathematics from Heilongjiang University, Harbin, China, the M.Sc. (with distinction) degree in applied mathematics from King’s College London, U.K. and the Ph.D. degree in applied mathematics from the University of Abertay Dundee, Dundee, U.K. She is currently a Professor of Information Systems and Management. Her research interests include data mining, artificial intelligence, pattern recognition, multivariance statistics, forecasting, and segmentations.
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Liu, P., Yu, H. & Cang, S. Trajectory Synthesis and Optimization of an Underactuated Microrobotic System with Dynamic Constraints and Couplings. Int. J. Control Autom. Syst. 16, 2373–2383 (2018). https://doi.org/10.1007/s12555-017-0192-7
- trajectory synthesis
- underactuated system
- vibro-driven microrobot