scholarly journals AI and ML for Human-Robot Cooperation in Intelligent and Flexible Manufacturing

2021 ◽  
pp. 95-127
Author(s):  
Manuel A. Ruiz Garcia ◽  
Erwin Rauch ◽  
Renato Vidoni ◽  
Dominik T. Matt
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Human Machine Interaction ◽  
Collaborative Robots ◽  
Robot Cooperation ◽  
Real Time Information ◽  
Cognitive Problems ◽  
Machine Interaction ◽  
Time Information ◽  
Environment Awareness

AbstractHuman–robot cooperation aims to increase the flexibilization of manufacturing systems. This requires safe human–machine interaction (e.g. with collaborative robots) as well as self and environment awareness capabilities to interact autonomously and smartly between humans and machines. Therefore, the goal of this chapter is to conceptualize and identify the set of real-time information processing and decision-making capabilities required for collaborative robots to be considered as a safe companion in the context of human–robot cooperation (HRC). In particular, the chapter provides an overview of appropriate artificial intelligence (AI) and machine learning (ML) concepts, formally introduces the concept of a safety-aware cyber-physical system and defines a general taxonomy for the perceptive and cognitive problems arising in the context of intelligent and flexible HRC.

scholarly journals Human-Computer-Machine Interaction for the Supervision of Flexible Manufacturing Systems: A Case Study

2020 ◽  
Vol 53 (2) ◽  
pp. 10550-10555
Author(s):  
Jose Daniel Hernandez ◽  
Edgar Schneider Cespedes ◽  
David Andres Gutierrez ◽  
David Sanchez-Londoño ◽  
Giacomo Barbieri ◽  
...  
Keyword(s):  
Flexible Manufacturing ◽  
Flexible Manufacturing Systems ◽  
Manufacturing Systems ◽  
Machine Interaction

scholarly journals ONLINE AND OFFLINE CONTROL OF COLLABORATIVE ROBOTS USED MIXED REALITY

2021 ◽  
Vol 7 (2) ◽  
pp. 61-66
Author(s):  
Jozef Husár ◽  
Lucia Knapčíková
Keyword(s):  
Mixed Reality ◽  
Current Trend ◽  
Manufacturing Companies ◽  
Human Machine Interaction ◽  
Collaborative Robots ◽  
Current Trends ◽  
Smart Glasses ◽  
Microsoft Hololens ◽  
Advanced Robotics ◽  
Machine Interaction

The presented article points to the combination of mixed reality with advanced robotics and manipulators. It is a current trend and synonymous with the word industry 5.0, where human-machine interaction is an important element. This element is collaborative robots in cooperation with intelligent smart glasses. In the article, we gradually defined the basic elements of the investigated system. We showed how to operate them to control a collaborative robot online and offline using mixed reality. We pointed out the software and hardware side of a specific design. In the practical part, we provided illustrative examples of a robotic workplace, which was displayed using smart glasses Microsoft HoloLens 2. In conclusion, we can say that the current trends in industry 4.0 significantly affect and accelerate activities in manufacturing companies. Therefore, it is necessary to prepare for the arrival of Industry 5.0, which will focus primarily on collaborative robotics.

scholarly journals Singularity Avoidance Control of a Non-Holonomic Mobile Manipulator for Intuitive Hand Guidance

Robotics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 14 ◽  
Author(s):  
Matthias Weyrer ◽  
Mathias Brandstötter ◽  
Manfred Husty
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Haptic Feedback ◽  
Controller Design ◽  
Essential Feature ◽  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Human Machine Interaction ◽  
Natural Approach ◽  
Robot Systems

Mobile manipulators are robot systems capable of combining logistics and manipulation tasks. They thus fulfill an important prerequisite for the integration into flexible manufacturing systems. Another essential feature required for modern production facilities is a user-friendly and intuitive human-machine interaction. In this work the goal of code-less programming is addressed and an intuitive and safe approach to physically interact with such robot systems is derived. We present a natural approach for hand guiding a sensitive mobile manipulator in task space using a force torque sensor that is mount close to the end effector. The proposed control structure is capable of handling the kinematic redundancies of the system and avoid singular arm configurations by means of haptic feedback to the user. A detailed analysis of all possible singularities of the UR robot family is given and the functionality of the controller design is shown with laboratory experiments on our mobile manipulator.

scholarly journals Programming Robots by Demonstration Using Augmented Reality

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5976
Author(s):  
Inês Soares ◽  
Marcelo Petry ◽  
António Paulo Moreira
Keyword(s):  
Augmented Reality ◽  
Manufacturing Systems ◽  
Industrial Revolution ◽  
Tracking System ◽  
Hand Movement ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Human Machine Interaction ◽  
Geometric Figures ◽  
Machine Interaction

The world is living the fourth industrial revolution, marked by the increasing intelligence and automation of manufacturing systems. Nevertheless, there are types of tasks that are too complex or too expensive to be fully automated, it would be more efficient if the machines were able to work with the human, not only by sharing the same workspace but also as useful collaborators. A possible solution to that problem is on human–robot interaction systems, understanding the applications where they can be helpful to implement and what are the challenges they face. This work proposes the development of an industrial prototype of a human–machine interaction system through Augmented Reality, in which the objective is to enable an industrial operator without any programming experience to program a robot. The system itself is divided into two different parts: the tracking system, which records the operator’s hand movement, and the translator system, which writes the program to be sent to the robot that will execute the task. To demonstrate the concept, the user drew geometric figures, and the robot was able to replicate the operator’s path recorded.

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