Task-Space Trajectory Tracking Control for Coordinated Manipulation Using Sampled Coupling Data | IEEE Journals & Magazine | IEEE Xplore

Task-Space Trajectory Tracking Control for Coordinated Manipulation Using Sampled Coupling Data


Abstract:

This letter studies the task-space synchronization control problem of networked manipulators which are commanded to track the desired task-space trajectories to achieve t...Show More

Abstract:

This letter studies the task-space synchronization control problem of networked manipulators which are commanded to track the desired task-space trajectories to achieve the coordinated manipulation transportation tasks in industrial and logistic applications. To guarantee the practical applicability and increase information transmission efficiency, sampled data-coupling strategy is utilized and the transmission delays as well as dynamics uncertainties are modelled explicitly. Firstly, the discrete-time-style synchronization error with sampled data is transferred into an equivalent continuous-time version with time-varying communication delays. Secondly, a distributed task-space tracking control law is presented based on the dynamic model by introducing the task-space end-position synchronization error for coordinated manipulation tasks of networked manipulators. Thirdly, a sufficient condition is derived from the Lyapunov-Krasovskii stability analysis approach to ensure the convergence of the dynamic control of each manipulator. By solving the proposed condition, the upper bound of the acceptable sampling period can be calculated. Simulational experiment results on a group of PUMA560 manipulators validate the task-space trajectory tracking performance, end-position synchronization performance and robustness to external force interference of the multiple-manipulator systems. To the best knowledge of the authors, this is the first letter which resolves the task-space tracking control of coordinated manipulators in the presence of coupling data sampling, transmission delays and dynamics model uncertainties.
Published in: IEEE Robotics and Automation Letters ( Volume: 6, Issue: 4, October 2021)
Page(s): 8434 - 8441
Date of Publication: 03 September 2021

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