Human and robot tasks in household environments include actions such as carrying an object, cleaning a surface, etc. These tasks are performed by means of dexterous manipulation, and for humans, they are straightforward to accomplish. Moreover, humans perform these actions with reasonable accuracy and precision but with much less energy and stress on the actuators (muscles) than the robots do. The high agility in controlling their forces and motions is actually due to "laziness", i.e. humans exploit the existing natural forces and constraints to execute the tasks. The above-mentioned properties of the human lazy strategy motivate us to relax the problem of controlling robot motions and forces, and solve it with the help of the environment. Therefore, in this work, we developed a lazy control strategy, i.e. task specification models and control architectures that relax several aspects of robot control by exploiting prior knowledge about the task and environment. The developed control strategy is realized in four different robotics use cases. In this work, the Popov-Vereshchagin hybrid dynamics solver is used as one of the building blocks in the proposed control architectures. An extension of the solver’s interface with the artificial Cartesian force and feed-forward joint torque task-drivers is proposed in this thesis. To validate the proposed lazy control approach, an experimental evaluation was performed in a simulation environment and on a real robot platform.


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    Titel :

    Lazy Robot Control by Relaxation of Motion and Force Constraints



    Erscheinungsdatum :

    2020-09-09


    Anmerkungen:

    Technical Report / Hochschule Bonn-Rhein-Sieg University of Applied Sciences. Department of Computer Science, 03-2020 ; ISSN 1869-5272



    Medientyp :

    Paper


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Schlagwörter :

    Klassifikation :

    DDC:    004 / 629




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