KURE: Kinematic universal remote interface a human centred remote robot control paradigm

Melidis, Christos; Marocco, Davide

doi:10.1109/smc.2016.7844716

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2021

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“…Some of these works track only the body segments that resulted in the most commonly adopted for the control of the considered robot in a pilot study 10,20,25 . Others fix the body segments to be tracked without user studies and derive a mapping by regressing human motion data over robot's motion data 26,27 . Recently, we propose a method to identify a BoMI mapping that automatically identifies and uses human motion patterns to control a robot and we validated it in the teleoperation of a fixed-wing drone 28 .…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Personalization of Body-Machine Interfaces to Control Diverse Robot Types

Macchini

Schiano

Floreano

2021

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Body-Machine Interfaces (BoMIs) for robotic teleoperation can improve a user’s experience and performance. However, the implementation of such systems needs to be optimized on each robot independently, as a general approach has not been proposed to date. Here, we present a novel machine learning method to generate personalized BoMIs from an operator’s spontaneous body movements. The method captures individual motor synergies that can be used for the teleoperation of robots. The proposed algorithm applies to people with diverse behavioral patterns to control robots with diverse morphologies and degrees of freedom, such as a fixed-wing drone, a quadrotor, and a robotic manipulator.

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