Autonomous space robots are and will be essential for future space missions like on-orbit satellite servicing, on-orbit assembly, active debris removal etc. Such missions require a base satellite equipped with deft manipulators for the on-orbit tasks. However, complexities and non-linearities associated with the control of such coupled space based systems presents difficulties in their feasible implementation. Lack of a fixed base arises serious problems in controlling the space manipulators for precision tasks like on-orbit servicing or capture of an orbiting space debris. This paper presents systematic modelling and control approaches for Rotation floating space robots in order to draw a comparison between them while tracking a moving target representing autonomous on-orbit tasks. We propose a Nonlinear Model Predictive Controller (NMPC) for the space robot in order to design an optimal path that the end-effector can follow while being controlled to reach to the target. To the best of the knowledge of the authors, such a controller has not been tested for a Rotation floating space robot before. Further, the current work implements and reviews two of the most commonly used Resolved Motion Rate Controller (RMRC) and Transpose Jacobian Cartesian (TJC) controller for Rotation floating space robots through the use of Generalized Jacobian Matrix (GJM). The results provide sufficient evidence of the superior performance of the nonlinear model predictive controller over the conventional controllers. Finally, the current work also implements the same nonlinear model predictive controller on a more popular state of the art Free floating space robot and compares it with the Rotation floating space robot. This paper thus brings all the floating modes under one umbrella in order to provide the reader a comprehensive description as well as a trade-off between performance and control requirements of the mentioned approaches.


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    Title :

    Free Floating and Rotation Floating approaches for Control of Space Robots: A comparative study


    Contributors:


    Publication date :

    2022-03-05


    Size :

    1485027 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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