Segmentation of model-free objects carried by human hand: Intended for human-robot interaction applications

Bdiwi, Mohamad; Kolker, Alexey; Suchy, Jozef; Winkler, Alexander

doi:10.1109/icar.2013.6766540

Cited by 4 publications

(1 citation statement)

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“…As a result, unexpected objects will not be recognized. For example, a hand-gesture recognition system based on HSV colour space was implemented for an automatic handing-over system between heavy-duty and human co-workers ( Bdiwi et al (2013b) ). This computer vision-based algorithm showed limits when tracking hand over reflective objects or objects with colour as human skin.…”

Section: Methodsmentioning

confidence: 99%

No-code robotic programming for agile production: A new markerless-approach for multimodal natural interaction in a human-robot collaboration context

et al. 2022

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Industrial robots and cobots are widely deployed in most industrial sectors. However, robotic programming still needs a lot of time and effort in small batch sizes, and it demands specific expertise and special training, especially when various robotic platforms are required. Actual low-code or no-code robotic programming solutions are exorbitant and meager. This work proposes a novel approach for no-code robotic programming for end-users with adequate or no expertise in industrial robotic. The proposed method ensures intuitive and fast robotic programming by utilizing a finite state machine with three layers of natural interactions based on hand gesture, finger gesture, and voice recognition. The implemented system combines intelligent computer vision and voice control capabilities. Using a vision system, the human could transfer spatial information of a 3D point, lines, and trajectories using hand and finger gestures. The voice recognition system will assist the user in parametrizing robot parameters and interacting with the robot’s state machine. Furthermore, the proposed method will be validated and compared with state-of-the-art “Hand-Guiding” cobot devices within real-world experiments. The results obtained are auspicious, and indicate the capability of this novel approach for real-world deployment in an industrial context.

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Section: Methodsmentioning

confidence: 99%