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A learning paradigm for motion control of mobile manipulators

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Abdessemed F., Monacelli E., Benmahammed K.
International Journal of Applied Mathematics and Computer Science
|
2006
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tom 16
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nr 4
475-484
EN
Motion control of a mobile manipulator is discussed. The objective is to allow the end-effector to track a given trajectory in a fixed world frame. The motion of the platform and that of the manipulator are coordinated by a neural network which is a kind of graph designed from the kinematic model of the system. A learning paradigm is used to produce the required reference variables for each of the mobile platform and the robot manipulator for an overall coordinate behavior. Simulation results are presented to show the effectiveness of the proposed scheme.
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On path following control of nonholonomic mobile manipulators

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Mazur A., Szakiel D.
International Journal of Applied Mathematics and Computer Science
|
2009
|
tom 19
|
nr 4
561-574
EN
This paper describes the problem of designing control laws for path following robots, including two types of nonholonomic mobile manipulators. Due to a cascade structure of the motion equation, a backstepping procedure is used to achieve motion along a desired path. The control algorithm consists of two simultaneously working controllers: the kinematic controller, solving motion constraints, and the dynamic controller, preserving an appropriate coordination between both subsystems of a mobile manipulator, i.e. the mobile platform and the manipulating arm. A description of the nonholonomic subsystem relative to the desired path using the Frenet parametrization is the basis for formulating the path following problem and designing a kinematic control algorithm. In turn, the dynamic control algorithm is a modification of a passivity-based controller. Theoretical deliberations are illustrated with simulations.
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