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Contribution à la commande en couple de robots redondants avec contrainte de RCM dans un contexte d'interaction physique humain-robot

Abstract : The work developped in this PhD thesis concerns the control of redundant torque-controlled robots,dealing with two main issues. Firstly, we study the presence of a RCM constraint imposed to the end-effector. We propose two control approaches to guarantee this kinematic constraint. In the first one, the constraint is performed in the null-space of a main task defined in cartesian coordinates(position). An explicit definition of the null-space dynamics is applied on this control approach, and provides a secondary priority order to the RCM constraint. The second approach allows to define the constraint as the main task, obtaining the highest priority level, or in any desired priority level,according to the needs of the application. Therefore, we propose a new kinematic formulation of the RCM constraint.Secondly, we study the physical interaction between the robot’s body and its environment (e.g. human) during the cartesian global task execution. A null-space compliance control strategy is then proposed in order to preserve the global task when the contacts occur. This strategy, defined for anthropomorphic 7-DOF robots, is formulated in swivel angle coordinates, which is a direct representation of the robot’s null-space. A desired feasible range for the swivel angle values is defined by the user, and a spring-damping compliance law is used to constraint the robot to remain within the feasible angle values range, despite the external forces applied to the robot’s body. Robot-assisted minimally invasive surgery has been used throughout this thesis as an example of application, allowing to demonstrate the usefulness of our contributions.
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Submitted on : Thursday, January 31, 2019 - 1:55:31 PM
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  • HAL Id : tel-02001865, version 1

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Juan Sebastian Sandoval Arevalo. Contribution à la commande en couple de robots redondants avec contrainte de RCM dans un contexte d'interaction physique humain-robot. Autre. Université d'Orléans, 2017. Français. ⟨NNT : 2017ORLE2064⟩. ⟨tel-02001865⟩

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