A natural interface based on intention prediction for semi-autonomous micromanipulation
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Manipulation at micro and nano scales is a particular case for remote handling. Although novel robotic approaches emerge, these tools are not yet commonly adopted due to their inherent complexity and their lack of user-friendly interfaces. In order to fill this gap, this work first introduces a novel paradigm dubbed semi-autonomous. Its aim is to combine full-automation and user-driven manipulation by sequencing simple automated elementary tasks following user instructions. To acquire these instructions in a more natural and intuitive way, we propose a “metaphor-free” user interface implemented in a virtual reality environment. A predictive intention extraction technique is introduced through a computational model inspired from cognitive sciences and implemented using a Kinect depth sensor. The model is compared in terms of naturalness and intuitiveness to a gesture recognition technique to detect user actions, in a semi-autonomous pick-and-place operation. It shows an improvement in user performance in duration and success of the task, and a qualitative preference for the proposed approach as evaluated by a user survey. The projected technique may be a worthy alternative to manual operation on a basic keyboard/joystick setup or even an interesting complement to the use of a haptic feedback arm.
KeywordsHCI Microrobotics Intention prediction Gesture recognition Kinect
Funding was provided by the French government research program “Investissements d’avenir” through SMART Laboratory of Excellence (Grant No. ANR-11-LABX-65) and Robotex Equipment of Excellence (Grant No. ANR-10-EQPX-44).
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