Conceptualising Assembly 4.0 through the Drone Factory

This paper aims to discuss the complexity of designing an assembly system according to industry 4.0. This is done by introducing the drone factory as a learning facility at the digital innovation hub SIILab. The paper discusses the areas of Operator-Organisation, Operator-Technologies, Technologies-Product and Product-Organisation in a current state and information support subsystem, IIoT architecture and hardware in the assembly 4.0 context

Automation of product packaging for industrial applications

[EN] This work presents a robotic-based solution devised to automate the product packaging in industrial environments. Although the proposed approach is illustrated for the case of the shoe industry, it applies to many other products requiring similar packaging processes. The main advantage obtained with the automated task is that productivity could be significantly increased. The key algorithms for the developed robot system are: object detection using a computer vision system; object grasping; trajectory planning with collision avoidance; and operator interaction using a force/torque sensor. All these algorithms have been experimentally tested in the laboratory to show the effectiveness and applicability of the proposed approach.This work has been partly supported by Ministerio de Economia y Competitividad of the Spanish Government [Grant No. RTC201654086 and PRI-AIBDE-2011-1219], by the Deutscher Akademischer Austauschdienst (DAAD) of the German Government (Projekt-ID 54368155) and by ROBOFOOT project [Grant No. 260159] of the European Commission.Perez-Vidal, C.; Gracia, L.; De Paco, J.; Wirkus, M.; Azorin, J.; De Gea, J. (2018). Automation of product packaging for industrial applications. International Journal of Computer Integrated Manufacturing. 31(2):129-137. https://doi.org/10.1080/0951192X.2017.1369165S12913731

Human-computer cooperation platform for developing real-time robotic applications

[EN] This paper presents a human-computer cooperation platform, which permits the coordination between the user and the tool to improve the development of real-time control applications (e.g., mobile robots). These applications have functional (robot objectives) and temporal requirements to accomplish (deadlines guarantee of tasks). The simulation tool has been designed in order to permit the testing and validation of these two requirements. To this end, the tool is composed of two independent simulators interconnected through a shared memory: the robot simulator (functional level) and the real-time task scheduler simulator (task execution level). Robotic applications can be defined with the robot simulator while the real-time scheduler simulator permits to analyze the schedulability of the robotic tasks. The real-time task simulator incorporates a flexible task model where the task temporal parameters (e.g., computation time) adapt to the requirements of the application (e.g., number of objects in scenes); thus, the use of the CPU is not overestimated. A key issue of the framework is the human-computer interface, which allows the monitoring of different parameters of the application: robot objectives, task schedule, robot speed, computation time, CPU utilization, deadline misses. The usefulness of the simulation tool is shown through different robotic navigation experiments. Finally, the simulation tool has been used to evaluate the proposed flexible model of tasks compared to a traditional fixed temporal parameters task model. Results show that the robot fulfills the objectives earlier, about 32% on average, and consumes on average about 15% less CPU to accomplish the objectives.Domínguez Montagud, CP.; Martínez-Rubio, J.; Busquets Mataix, JV.; Hassan Mohamed, H. (2019). Human-computer cooperation platform for developing real-time robotic applications. The Journal of Supercomputing. 75(4):1849-1868. https://doi.org/10.1007/s11227-018-2343-4S18491868754Dominguez C, Hassan H, Crespo A (2007) Real-time embedded architecture for pervasive robots. In: The 2007 International Conference on Intelligent Pervasive Computing (IPC 2007), pp 531–536Audsley NC, Burns A, Davis RI, Tindell KW, Wellings AJ (1995) Fixed priority pre-emptive scheduling: an historical perspective. Real Time Syst 8(2–3):173–198Stankovic JA, Lee I, Mok A, Rajkumar R (2005) Opportunities and obligations for physical computing systems. Computer 38(11):23–31Zhen Z, Qixin C, Lo C, Lei Z (2009) A CORBA-based simulation and control framework for mobile robots. Robotica 27(3):459Ferretti G, Magnani G, Porrati P, Rizzi G, Rocco P, Rusconi A (2008) Real-time simulation of a space robotic arm. In: IROSQadi A, Goddard S, Huang J, Farritor S (2005) A performance and schedulability analysis of an autonomous mobile robot. In: 17th Euromicro Conference on Real-Time Systems (ECRTS’05), pp 239–248Goud GR, Sharma N, Ramamritham K, Malewar S (2006) Efficient real-time support for automotive applications: a case study. In: 12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’06), pp 335–341Pedreiras P, Luis A (2003) The flexible time-triggered (FTT) paradigm: an approach to QoS management in distributed real-time systems. In: Proceedings International Parallel and Distributed Processing Symposium, p 9Li H, Sweeney J, Ramamritham K, Grupen R, Shenoy P (2003) Real-time support for mobile robotics. In: The 9th IEEE Real-Time and Embedded Technology and Applications Symposium. Proceedings, pp 10–18Chetto H, Chetto M (1989) Some results of the earliest deadline scheduling algorithm. IEEE Trans Softw Eng 15(10):1261–1269Liu R, Zhang X (2017) Systems of natural-language-facilitated human-robot cooperation: a review. arXiv:1701.08269v2Tsarouchi P, Makris S, Chryssolouris G (2016) Human–robot interaction review and challenges on task planning and programming. Int J Comput Integr Manuf 29(8):916–931Moniz A (2013) Organizational concepts and interaction between humans and robots in industrial environments. In: IEEE-RAS-IARP Joint Workshop on Technical Challenges for Dependable Robots in Human Environment, TokyoMayer MP, Odenthal B, Faber M, Winkelholz C, Schlick CM (2014) Cognitive engineering of automated assembly processes. Hum Factors Ergon Manuf Serv Ind 24(3):348–368Agostini A, Torras C, Wörgötter F (2011) Integrating task planning and interactive learning for robots to work in human environments. In: IJCAIKwon W, Suh I (2014) Planning of proactive behaviors for human–robot cooperative tasks under uncertainty. Knowl Based Syst 72:81–95Chen F, Sekiyama K, Sasaki H, Huang J, Sun B, Fukuda T (2011) Assembly strategy modeling and selection for human and robot coordinated cell assembly. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 4670–4675Gombolay M, Wilcox R, Diaz A, Yu F (2013) Towards successful coordination of human and robotic work using automated scheduling tools: an initial pilot study. In: Proceedings of Robotics: Science and Systems, Human–Robot Collaboration WorkshopGombolay MC, Gutierrez RA, Clarke SG, Sturla GF, Shah JA (2015) Decision-making authority, team efficiency and human worker satisfaction in mixed human–robot teams. Auton Robots 39(3):293–312Frontoni E, Mancini A, Caponetti F, Zingaretti P (2006) A framework for simulations and tests of mobile robotics tasks. In: 2006 14th Mediterranean Conference on Control and Automation, pp 1–6I. Embarcadero Technologies, C++ Builder 10.2. https://www.embarcadero.com

A Mixed-Integer Linear Programming Formulation for Human Multi-Robot Task Allocation

In this work, we address a task allocation problem for human multi-robot settings. Given a set of tasks to perform, we formulate a general Mixed-Integer Linear Programming (MILP) problem aiming at minimizing the overall execution time while optimizing the quality of the executed tasks as well as human and robotic workload. Different skills of the agents, both human and robotic, are taken into account and human operators are enabled to either directly execute tasks or play supervisory roles; moreover, multiple manipulators can tightly collaborate if required to carry out a task. Finally, as realistic in human contexts, human parameters are assumed to vary over time, e.g., due to increasing human level of fatigue. Therefore, online monitoring is required and re-allocation is performed if needed. Simulations in a realistic scenario with two manipulators and a human operator performing an assembly task validate the effectiveness of the approach.Comment: Accepted to 2021 IEEE International Conference on Robot and Human Interactive Communication (RO-MAN

A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

In this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception system specifically designed for the detection of social and emotional cues. It will be explained how the information extracted by this specific kind of framework is particularly suitable for social robotics applications and how the system has been conceived in order to be used in human-robot interaction scenarios

Collection and analysis of human upper limbs motion features for collaborative robotic applications

Background: The technologies of Industry 4.0 are increasingly promoting an operation of human motion prediction for improvement of the collaboration between workers and robots. The purposes of this study were to fuse the spatial and inertial data of human upper limbs for typical industrial pick and place movements and to analyze the collected features from the future perspective of collaborative robotic applications and human motion prediction algorithms. (2) Methods: Inertial Measurement Units and a stereophotogrammetric system were adopted to track the upper body motion of 10 healthy young subjects performing pick and place operations at three different heights. From the obtained database, 10 features were selected and used to distinguish among pick and place gestures at different heights. Classification performances were evaluated by estimating confusion matrices and F1-scores. (3) Results: Values on matrices diagonals were definitely greater than those in other positions. Furthermore, F1-scores were very high in most cases. (4) Conclusions: Upper arm longitudinal acceleration and markers coordinates of wrists and elbows could be considered representative features of pick and place gestures at different heights, and they are consequently suitable for the definition of a human motion prediction algorithm to be adopted in effective collaborative robotics industrial applications

Specifying task allocation in automotive wire harness assembly stations for Human-Robot Collaboration

Wire harness assembly is normally a manual assembly process that poses\ua0ergonomic\ua0challenges. As a consequence of the rapidly expanding electrification of vehicles and transportation systems, the demand for wire harnesses can be expected to grow radically, further increasing assembly operator challenges. Thus, automating this assembly process is highly prioritised by production engineers. The rapid development of industrial robot technology has enabled more human-robot collaboration possibilities, simplifying the automation of wire harness process tasks. However, successful automation applications involving humans require efficient and safe allocation of tasks between humans and technology. Unfortunately, present assembly system design methods may be obsolete and insufficient in light of the capabilities of emerging automation technologies such as collaborative robots. This paper presents a design and specification methodology for human-centred\ua0manufacturing systems\ua0and focuses on collaborative assembly operations in complex production systems. A case study on human-robot collaboration provides an application example from a wire-harness collaborative assembly process. The proposed design methodology combines\ua0hierarchical task analysis\ua0with assessments of cognitive and physical Levels of Automation (LoAc\ua0and LoAp). The assessments are then followed by evaluations of the Levels of human-robot Collaboration (LoC) and the Levels of operator Skill requirements (LoSr) respectively. A task allocation\ua0matrix supports\ua0the identification of possible combinations of automation and collaboration solutions for a human-centred and collaborative wire harness assembly process. System designers and integrators may utilise the design and specification methodology to identify the potential and extent of human-robot collaboration in collaborative manufacturing assembly operations

The Importance of Risk Management for the Introduction of Modern Warehouse Technologies

The purpose of the study is to determine whether the presence of risk management in a warehouse requires the implementation of modern warehouse technology. On the basis of the literature analysis, it was possible to determine that there is a correlation between the presence of the highest level of risk management and the use of modern warehouse technology in individual warehousing processes. For this purpose, a statistical analysis was carried out on a sample of companies operating in the Slovenian automotive industry. The results did not reveal a tangible correlation between the presence of risk management with the use of individual modern warehouse technology, the motivation for its use and errors in its use. The results of the study therefore, highlight the problems that are present in the warehousing system of the Slovenian companies in the automotive industry, which are related to substandard technological equipment in the warehouses and to the discrepancy between the level of manufacturing automation and the level of warehousing automation. The results are important for the Slovenian automotive industry in terms of the implementation of modern warehouse technology in the high-tech automotive industry.</p