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Optimized Interaction Control for Robot Manipulator Interacting With Flexible Environment

Xing Liu, Shuzhi Sam Ge, Fei Zhao, Xuesong Mei

2020IEEE/ASME Transactions on Mechatronics31 citationsDOI

Abstract

In this article, a novel interactioncontrol is presented to resolve the optimized robot-environment interaction control problems subject to flexible environment with unknown dynamics parameters. A cost function measuring the trajectory tracking error as well as the noninertial interaction force is defined. A complete state-space equation considering the robot desired trajectory, object dynamics and position parameters is also presented to address the optimized robot-environment interaction control problem. The improved Q-learning method is developed as the fundamental of the proposed control to deal with the challenges brought by the unknown environment dynamics and the reference position of the robot desired trajectory. Simulation and experimental studies verify the validity of the presented method.

Topics & Concepts

TrajectoryRobotPosition (finance)Control theory (sociology)Computer scienceControl engineeringObject (grammar)Robot controlTracking (education)Control (management)Function (biology)Artificial intelligenceMobile robotEngineeringPhysicsFinanceEconomicsBiologyPedagogyAstronomyEvolutionary biologyPsychologyRobot Manipulation and LearningAdaptive Dynamic Programming ControlAdvanced Control Systems Optimization
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