Determining the externally-induced motion of a soft robot in minimally-invasive procedures is highly challenging and commonly demands specific tools and dedicated sensors. Intrinsic force sensing paired with a model describing the robot's compliance offers an alternative pathway which relies heavily on knowledge of the characteristic mechanical behaviour of the investigated system. In this work, we apply quasi-static intrinsic force sensing to a miniature, parallel soft robot designed for endoluminal ear interventions. We characterize the soft robot's nonlinear mechanical behaviour and devise methods for inferring forces applied to the actuators of the robot from fluid pressure and volume information of the working fluid. We demonstrate that it is possible to detect the presence of an external contact acting on the soft robot's actuators, infer the applied reaction force with an accuracy of 28.1 mN and extrapolate from individual actuator force sensing to determining forces acting on the combined parallel soft robot when it is deployed in a lumen, which can be achieved with an accuracy of 75.45 mN for external forces and 0.47 Nmm for external torques. The intrinsically-sensed external forces can be employed to estimate the induced motion of the soft robot in response to these forces with an accuracy of 0.11 mm in translation and 2.47 in rotational deflection. The derived methodologies could enable designs for more perceptive endoscopic systems and pave the way for developing sensing and control strategies in endoluminal and transluminal soft robots.


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    Titel :

    Intrinsic Force Sensing for Motion Estimation in a Parallel, Fluidic Soft Robot for Endoluminal Interventions


    Beteiligte:
    Lindenroth, Lukas (Autor:in) / Merlin, Jeref (Autor:in) / Bano, Sophia (Autor:in) / Manjaly, Joseph G (Autor:in) / Mehta, Nishchay (Autor:in) / Stoyanov, Danail (Autor:in)

    Erscheinungsdatum :

    2022-10-01


    Anmerkungen:

    IEEE Robotics and Automation Letters , 7 (4) pp. 10581-10588. (2022)


    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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