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The rapid advancement of robotics and artificial intelligence paves the way for collaborative robotics to revolutionise industrial operations. Collaborative robotics can bring significant improvements in productivity, efficiency, and safety. Recently, the concept of Symbiotic Human-Robot Collaboration (SHRC) has emerged within the field of collaborative robotics, emphasising the seamless and adaptive integration of human and robotic capabilities within a shared workspace to optimise overall production performance. However, existing collaborative systems frequently face difficulties in establishing dynamic relationships with humans and adapting to evolving conditions, ultimately restricting their overall potential. This paper investigates the essential features required for collaborative workstations to enable SHRC. Moreover, with the aim of fully harnessing the power of collaborative robotics, the paper introduces a design methodology that supports the development of symbiotic workstations for specific assembly operations. A real-world case study is provided, demonstrating the practical implementation and benefits of the proposed design approach. [ABSTRACT FROM AUTHOR]

Due to the increasing trends of individualization and variant diversity, cobotic production systems are becoming more important. However, cobots are hardly used in small and medium-sized enterprises (SME) because of a lack in expertise, experience or resources. In order to be able to assess whether the use of a cobot is reasonable, there are already many methods in research with different focuses such as ergonomics, productivity or economic efficiency. However, many methods are not targeted for use by SME, thus still require the involvement of experts, and often only consider economic efficiency without consideration of human-centered aspects. Furthermore, these are mostly not integrated into commonly used process planning tools. This work provides an overview of methods for automated analysis of assembly processes in HRC. We present a method for HRC process analysis with an individual weighting of fatigue, time, costs and safety that can be set depending on an application-specific focus defined by the user. It allows non-experts to perform a process analysis based on the individual weighting and a digital twin of the workstation. An evaluation method developed for this purpose calculates the benefit of a cobot in the analyzed process depending on the preset focus. To keep the effort low, the method includes a workflow to easily create a digital twin of the workplace with sufficient accuracy. In addition to the pre-estimation of the human-cobot process, the method allows an easy planning of collaborative production processes, which is why we suggest a conceptual integration into a process planning and control framework. The proposed approach is demonstrated in an use case by analyzing the potential for introduction of collaborative robots for the production of currently manually assembled solar inverters. [ABSTRACT FROM AUTHOR]

A significant shift from traditional lines to reconfigurable and reprogrammable robotic cells has occurred in Industry 4.0. Collaborative robots can be used for automating several tasks for improving Human-Machine Interface (HMI). The ability of a robot carrying out different tasks is proportional to the tools that it can use, thus it is crucial that robots are equipped with systems enabling efficient tool changing. Therefore, in this paper an automatic tool changer system is proposed. Based on Finite Element Analysis (FEA) of the design and the specifications, a 3D printed prototype was made and tested on a UR 10 Collaborative Robot. [ABSTRACT FROM AUTHOR]

From drug delivery in hospitals to transportation of goods in warehouses, mobile robotic platforms have a wide variety of applications in industry today. The integration of mobile platforms with a manipulator opens up the possibility of more practical applications. However, this also introduces a new problem regarding the localisation accuracy of the platform, which in turn affects the accuracy of the manipulation. This paper details a comparative study of different strategies for improving the accuracy of pick and place tasks using a mobile robotic platform with an integrated arm. These strategies include fine positioning, LiDAR feedback and vision system feedback. [ABSTRACT FROM AUTHOR]

With the rise of Industry 4.0 technological trends, there is a growing tendency in manufacturing automation towards collaborative robots. Human-robot collaboration (HRC) is motivated by the combination of complementary human and robot skills and intelligence, which can increase productivity, flexibility and adaptability. However, it is still challenging to achieve safe and efficient human-robot collaborative systems due to the dynamics of human presence, uncertainties in the dynamic environment, and the need for adaptability. Such uncertainties could relate to the human-robot capabilities and availability, parts positioning, unexpected obstacles, etc. This paper develops time-based simulations and event-based simulations to model and analyse the dynamic factors in human-robot collaboration systems. The novelty of this work is the systematic modelling and analysis of dynamic factors in HRC manufacturing scenarios through the development of digital simulations of human-robot collaboration scenarios while considering the dynamic nature of humans and environments. A real-world industrial case study was redesigned into a collaborative workstation. The simulated scenario is developed using the software called Tecnomatix Process Simulate, which can help to visualise the dynamic factors and analyse the impact of the factors on the HRC. The simulation illustrates and analyses possible uncertainties in human-robot industrial collaborative workstations, which can contribute to the future design of HRC industrial workstations and the optimisation of productivity. [ABSTRACT FROM AUTHOR]

The growing variety of products brings various workpieces, which have complex welding seams that cannot be welded by current welding robots fixed in the welding stations or carried by the gantry. Therefore, this paper proposes a mobile collaborative welding system composed of an AGV (Automated Guided Vehicle) and a 6-DOF (Six-Degree-of-Freedom) collaborative robot. Considering the complex welding seams, a mobile collaborative welding method is proposed. The collaborative welding method includes three steps, i.e., welding seam acquisition, welding seam classification and segmentation, and welding task allocation. The authors present a new approach to acquire the spatial position characteristics of welding seams based on the human-machine collaboration. According to the spatial position characteristics of the welding seams, the welding type identification and classification segmentation can be obtained. Finally, the welding tasks of the robot and AGV can be allocated. [ABSTRACT FROM AUTHOR]

Collaborative robots and personalised human-automation load balancing strategies may be able to empower workers with cognitive disabilities to carry out complex assembly tasks. To design such assembly cells, it is necessary to investigate the human factors associated with this user group in relation to the technology proposed. We present a qualitative pilot user study in which an assembly worker with cognitive disabilities and multidisciplinary experts meet a collaborative robot in the context of routine assembly jobs. We draw requirements for the design of such cells and we contrast them with design requirements for regular workforce. [ABSTRACT FROM AUTHOR]

Collaborative human-robot multi-component systems intended for industrial processes are designed and implemented to meet requirements of productivity in the process and safety in the workplace. If these systems are to gain broad adoption and acceptance in the workplace, it is also essential that they provide the best possible user experience (UX) for the collaborating human worker. This paper reports data from an early-stage qualitative user study with two distinct groups of potential users of collaborative robots in industry: professionals from industry and students in vocational training. Attitudes towards such systems are analyzed, and key concerns and expectations are identified. [ABSTRACT FROM AUTHOR]

The ‘water leak test’ in an automotive final assembly line is often a significant cost factor due to its labour intensive nature. This is particularly the case for premium car manufacturers as each vehicle is watered and manually inspected for leakage. This paper delivers an approach that optimises the efficiency and capability of the test process by using a new automated in-line inspection system whereby thermographic images are taken by a lightweight robot system and then processed to locate the leak. Such optimisation allows the collaboration of robots and manual labour which in turn enhances the capability of the process station. [ABSTRACT FROM AUTHOR]

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Objective: This paper is to analyze the performance of the control system of collaborative robots based on cognitive computing technology. Methods: This study combines cognitive computing and deep belief network algorithms with collaborative robots to construct a cognitive computing system model based on deep belief networks, which is applied to the control system of collaborative robots. Further, the simulation is used to compare and analyze the algorithm performance of deep belief network (DBN), multilayer perceptron (MLP) and the cognitive computing system model of deep belief network and linear perceptron (DBNLP) proposed in this study. Results: The results show that compared with the DBN and MLP algorithms, the DBNLP algorithm model has a significantly lower error rate in the number of repetitions of the training set, the number of hidden neurons, and the number of network layers. And the number of task backlog, the number of resources to be allocated and the time consumption are less, as well as the accuracy is high. After comparing and analyzing the changes in the estimated value of Ex (expected value), En (entropy value) and He (hyper entropy value), it is found that the estimated value of the DBNLP algorithm model is closer to the true value than that of the DBN and MLP algorithms. Conclusion: The application of the DBNLP algorithm model to collaborative robots can significantly improve its accuracy and safety, providing an experimental basis for the performance improvement of later collaborative robots. • Analyze the performance of the control system of collaborative robots based on cognitive computing. • This study combines cognitive computing and deep belief network algorithms with collaborative robots to construct a cognitive computing system model based on deep belief networks, which is applied to the control system of collaborative robots. • The simulation is used to compare and analyze the algorithm performance of deep belief network (DBN), multilayer perceptron (MLP) and the cognitive computing system model of deep belief network and linear perceptron (DBNLP) proposed in this study. [ABSTRACT FROM AUTHOR]