In the light of factories of the future, to ensure productive and safe interaction between robot and human coworkers, it is imperative that the robot extracts the essential information of the coworker. We address this by designing a reliable framework for real-time safe human-robot collaboration, using static hand gestures and 3D skeleton extraction. OpenPose library is integrated with Microsoft Kinect V2, to obtain a 3D estimation of the human skeleton. With the help of 10 volunteers, we recorded an image dataset of alphanumeric static hand gestures, taken from the American Sign Language. We named our dataset OpenSign and released it to the community for benchmarking. Inception V3 convolutional
This paper introduces BAZAR, a collaborative robot that integrates the most advanced sensing and actuating devices in a unique system designed for the Industry 4.0. We present BAZAR's three main features, which are all paramount in the factory of the future. These features are: mobility for navigating in dynamic environments, interaction for operating side-by-side with human workers and dual arm manipulation for transporting and assembling bulky objects. Keywords Efficient, flexible and modular production • Robotics • Smart Assembly • Human-robot co-working • Real industrial world case studies • Digital Manufacturing and Assembly System • Machine Learning.
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