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The current generation of Industry 4.0 involves the integration of automation and data in manufacturing, while the upcoming generation, Industry 5.0, aims to enable seamless interaction between humans, robots, and machines for sustainable and personalized product and service creation. This necessitates manufacturing components according to customer wishes, leading to frequent changes in the production line. In this context, automation proves unsustainable and could be addressed through Human–Robot Cooperation. In this paper, an Extended Reality (XR)-based Human–Robot Interaction with haptic feedback has been proposed to assist users in remotely performing tasks. The haptic feedback, generated using the Artificial Potential Field method, aids users in controlling robots without collisions. This paper introduces a multimodal XR-based framework for effective communication between humans and robots, utilizing vision models to provide information about the remote side to local users. This seamless communication is facilitated through multiple modalities such as haptic, speech, visual, and text. The system's effectiveness through pick-and-place activities and adaptation to it for complex industry use cases such as peg in the hole and welding are further evaluated. The results demonstrate the system's efficacy in two specific human–robot collaborative scenarios in industries: arc welding and assembly tasks. [ABSTRACT FROM AUTHOR]

Collaborative robots have open new ways of designing assembly processes, thanks to their ability to share work space with operators. not only may they support the economical performance, but they can also improve the overall ergonomics. Building on existing work on task allocation problems, the authors study further the collaboration opportunities between operator and robot, namely cooperation phases (type of collaboration where both operator and robot act on the same work piece). This work proposes a new formulation of the related problem, and solutions are sought through heuristics methods, to investigate whether concurrent usage of different collaboration modes delivers better performance. The results indicate that cooperation mode enables higher process performances while controlling ergonomic risks. With a concern for real-life application, it has been applied on a real case study to verify its applicability. [ABSTRACT FROM AUTHOR]

In the European manufacturing industry, production batches are decreasing, resulting in an increase in required changeovers. Companies are pushed to respond quickly and cost-efficient to changing markets. One way for Small and Medium sized Enterprises (SMEs) to become more agile, is to incorporate industrial robots in their production processes; larger enterprises already use this versatile piece of equipment for large batch sizes. To do so, a new perspective and approach is required, tailored to dynamic manufacturing systems in which production systems and components can be easily reconfigured, altered, swapped or replaced. A modular system architecture was developed within project SInBot upon which challenges in dynamic cooperation between robots and humans were projected. The developed system uses decentralized control and distributed intelligence, linked through an extensible, flexible, and fault-tolerant communication architecture. The rapidly growing complexity of traditional systems is compared to its decentralized counterpart to illustrate some of the many advantages of this new system architecture. A manufacturing scenario analogue is discussed and the approach to verify the performance of inner-system components, as well as the benefits of this approach. Key challenges that are encountered in implementing the cooperation into the current industrial environments are identified and projected upon the verification system. [ABSTRACT FROM AUTHOR]

This paper discusses a method for the coordination of assembly tasks requiring the cooperation of humans with a robot. A ROS based architecture is used. The assembly sequence of these tasks and their characteristics are modeled in a neutral XML format generated off-line. A ROS based framework in order for different modules to communicate and coordinate their actions through the exchange of messages. The human is able to review the past and upcoming tasks in a graphical user interface. The human and robot coexist in a fenceless cell where safety is ensured using a certified camera system. This framework is applied to an automotive case study using the Process Simulate tool for the execution of assembly tasks. [ABSTRACT FROM AUTHOR]

Small and Medium sized Enterprises (SMEs) in Europe struggle to incorporate industrial robots in their production environments, while large enterprises use these robots for large batch production only. The paradigm shift from mass production to mass personalization decreases batch sizes and changes the approach to implementation of industrial robots in manufacturing environments. It also opens doors for SMEs to further incorporate robots in their production environments. The goal of this research is to evaluate the suitability of a data-centric, distributed, decentralized manufacturing system for cooperation between robots and humans. A case is presented featuring cooperation between robots and humans. A control system is proposed based on distributed intelligence and decentralized control, to handle the rapidly expanding complexity in dynamic manufacturing environments. The communication in such a distributed environment is provided by a Data Distribution Service system; an extendible, flexible approach to communication. Key issues that are encountered in implementing the cooperation into the current industrial environments are identified. The proposed control system is projected on the case and evaluated for application suitability and expected performance. [ABSTRACT FROM AUTHOR]