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

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.

Towards safety4.0: A novel approach for flexible human-robot-interaction based on safety-related dynamic finite-state machine with multilayer operation modes.

In the era of Industry 4.0 and agile manufacturing, the conventional methodologies for risk assessment, risk reduction, and safety procedures may not fulfill the End-User requirements, especially the SMEs with their product diversity and changeable production lines and processes. This work proposes a novel approach for planning and implementing safe and flexible Human-Robot-Interaction (HRI) workspaces using multilayer HRI operation modes. The collaborative operation modes are grouped in different clusters and categorized at various levels systematically. In addition to that, this work proposes a safety-related finite-state machine for describing the transitions between these modes dynamically and properly. The proposed approach is integrated into a new dynamic risk assessment tool as a promising solution toward a new safety horizon in line with industry 4.0.