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Registration protocol for PRISMA scoping review that comprehensively overviews current sensor-enabled safety systems for human-robot collaboration in the manufacturing industry.

As robots' use increases in every sector of human life, the demand for cheap and efficient robots has also enlarged. The use of two or more simple robot is preferable to the use of one sophisticated robot. The agriculture industry can benefit from installing a robot, from seeding to the packaging of the product. A precise analysis is required for the installation of two collaborative robots. This paper discusses the motion control analysis of two collaborative arms robots in the fruit packaging system. The study begins with the relative motion analysis between two robots, starting with kinematics modeling, image processing for object detection, and the Fuzzy Logic Controller's design to show the relationship between the robot inputs and outputs. The analysis is carried out using SCILAB, open-source software for numerical computing engineering. This paper is intended as the initial analysis of the feasibility of the real experimental system.

In this paper, a new comprehensive dynamic friction model for a collaborative industrial robot joint that considers the velocity, temperature, and load torque is proposed. The variation of load-dependent friction among the four-quadrant operation depending on the sign of load-torque and speed is studied. The new model’s passivity property is analyzed to obtain a physically meaningful and experimentally identified friction model. A sufficient condition is presented in terms of a simple algebraic inequality involving the parameters of the model. The model parameter identification procedure and validation of model effectiveness are demonstrated experimentally on a commercial collaborative robot manipulator. Moreover, the proposed friction model’s benefits are demonstrated in two different robot applications: friction compensation and direct teaching (smooth lead-through programming) applications. Significant tracking performance improvement in the root-mean-square errors up to 76% was achieved with the proposed friction model compared to the uncompensated cases in the friction compensation application. In the direct teaching application, the new model, which precisely estimates joint friction, results in a significant decrease in interaction forces up to 66%. These experimental results validate the performance of the proposed friction model.

Smart factories should be able to respond to catastrophic situations proactively, such as recalls caused by production line disruptions and equipment failures. Therefore, the necessity for predictive maintenance technology, such as fault detection or diagnosis of equipment has increased in recent years. In particular, predicting the faults of collaborative robots is becoming increasingly crucial because smart factories pursue efficient collaboration between humans and devices. However, collaborative robots have the characteristic of executing programmable motions designed by an operator, rather than performing fixed tasks. If existing fault diagnosis methods are applied to non–fixed programmable motions, problems arise in terms of setting absolute criteria for fault analysis, interpreting the meanings of detected values, and fault tracking or fault cause analysis. Therefore, we propose a method of programmable motion-fault detection by analyzing motion residuals to solve the three problems mentioned above. The proposed method can expand the fault diagnostic range of collaborative robots.

In this paper, a mobile manipulation system for automatized logistic applications is presented. The robotic system is specifically designed for depalletizing/palletizing tasks, namely is product extraction from homogeneous pallets and assembly of new heterogeneous pallets. The robotic system is mainly composed by an autonomous vehicle, a collaborative robotic arm and a lifting device, which is able to collect products from different pallet layers. The handling strategy is not based on lifting items, as in classical pick-and-place operations, but on dragging them aboard the mobile vehicle. As the payload weight is not supported by the arm, the overall robotic system is very light compared to the manipulated items, which is a paramount benefit for a mobile collaborative application. This paper presents the mechanical design, the hardware selection and the experimentation in a laboratory scenario, thus demonstrating the effectiveness of the proposed manipulation strategy.

This paper presents a novel real-time collision-free speed alteration strategy using a danger index and an elite real-coded genetic algorithm (ERGA) for environments in which humans and robots coexist or cooperate, in order to guarantee the safety of an operator who works with a collaborative robot. A danger index based on ellipsoid modeling of the operator and robot describes the degree of safety during human-robot interactions. The ERGA and a penalty function are used to solve the constrained nonlinear optimization problem to change the handling speed of the robot. Comparative simulation results show the superiority of the proposed method by comparing to two existing methods. The applicability of the proposed method is verified using two experiments involving a 6-DoF industrial manipulator with an EtherCAT network protocol, an RGB-D sensor and a real-time operation system.

International audience; The collaborative robot (cobot) is a technology contributing to the industrial revolution Industry 4.0. Indeed, cobots’ flexibility and their easy-to-use solutions fill a gap with traditional robots to robotize manufacturing of products with low volume and high mix profiles. Parts needed to manufacture a product must first be presented to the cobot, so that afterwards it can perform operations such as assembly. The paper classifies the current part presenters. Then, a methodology is proposed to select the best presenter based on the characteristics of the parts and the workstation. To be aligned with markets requiring a high mix of products frequently renewed, the development times for part presenter design and for cobot programming are new data to select the best presenter. Indeed, at every part redesign, the part presenter changes and the cobot is reprogrammed. These two times are depreciated based on the lifespan quantity of the part. Lifespan quantity is the number of the same parts, which are dropped-off on the part presenter during the part’s lifespan, i.e. until its redesign. A concrete industrial use case is explained to test the methodology. Results conclude that a tray pattern is the best part presenter, except for parts with low lifespan quantity. Lifespan quantity of the part appears to be a significant parameter when deciding the best part presenter.

Collaborative robots (cobots) are important components of the Industry 4.0 paradigm and smart manufacturing. Cobots are known for their ability to interact with the operators in a shared workspace....

Collaborative robots are currently deployed in professional environments, in collaboration with professional human operators, helping to strike the right balance between mechanization and manual intervention in manufacturing processes required by Industry 4.0. In order to support human operators, cobots need to be able to constantly perceive their activities and follow them. In this paper, the contribution of gesture recognition and pose estimation to the smooth introduction of cobots into an industrial production line is described, with a view to performing actions in parallel with the human operators and enabling interaction between them. For this to be achieved, a collaboration protocol that uses Machine Learning algorithms, wearables and sensors is established. The use-case of this work is concerned with LCD TV assembly on the production line of an appliance manufacturer. Both parts of the operation are currently performed manually. The introduction of a human-robot interaction system with spatiotemporal adaptive cobot behavior is presented, to which the first part of the above-mentioned operation is assigned, strengthening the production line. Gesture recognition, pose estimation, physical interaction and sonic notification create a multimodal human-robot interaction system. Five experiments were performed, in order to compare the different types of interaction possible. Physical interaction was achieved using force sensor of the cobot. Pose estimation through a skeleton-tracking algorithm provided the cobot with human pose information and made it spatially adjustable. Sonic notification was added in case of any unexpected incidents. A real-time gesture recognition module was used for the recognition and interpretation of the gestures that constitute the TV assembly routine to be performed by the cobot. Finally, a combination of all the modalities was investigated. Gesture recognition was implemented through a Deep Learning architecture consisting of Convolutional layers, trained in an egocentric view. This constitutes an added value in this work, as it affords the potential of recognizing gestures independently of the anthropometric characteristics and the background. Common metrics derived from the literature were used for the evaluation of the proposed system. The opinion of the human operator was measured through a questionnaire that concerned the various affective states of the operator during the collaboration.

Human-robot interaction has received a lot of attention as collaborative robots became widely utilized in many industrial fields. Among techniques for human-robot interaction, collision identification is an indispensable element in collaborative robots to prevent fatal accidents. This paper proposes a deep learning method for identifying external collisions in 6-DoF articulated robots. The proposed method expands the idea of CollisionNet, which was previously proposed for collision detection, to identify the locations of external forces. The key contribution of this paper is uncertainty-aware knowledge distillation for improving the accuracy of a deep neural network. Sample-level uncertainties are estimated from a teacher network, and larger penalties are imposed for uncertain samples during the training of a student network. Experiments demonstrate that the proposed method is effective for improving the performance of collision identification.

Highlights • As the COVID-19 pandemic expands, causing a shortage of medical supplies, a key piece of equipment has been ventilator. • The manufacturing systems of today are designed for mass production with minimum product variability at competitive cost • Besides high potential of cobotic automation, their application in assembly is limited • Collaborative robots can form reconfigurable manufacturing systems and can ramp up production. • Modularization, plug-&-play hardware and digital twins are key enablers for fast (re) configuration of cobots., As the COVID-19 pandemic expands, the shortening of medical equipment is swelling. A key piece of equipment getting far-out attention has been ventilators. The difference between supply and demand is substantial to be handled with normal production techniques, especially under social distancing measures in place. The study explores the rationale of human-robot teams to ramp up production using advantages of both the ease of integration and maintaining social distancing. The paper presents a model for faster integration of collaborative robots and design guidelines for workstations. The scenario is evaluated for an open source ventilator through continuous human-robot simulation and amplification of results in a discrete event simulation.

International audience; Accepted version freely available here: [ http://bit.ly/2qlyjJ6 ] Online version via SpringerLink: [ http://link.springer.com/article/10.1007/s10846-019-01110-1 ] Abstract: This paper presents a new bi-objective safety-oriented path planning strategy for robotic manipulators. Integrated into a sampling-based algorithm, our approach can successfully enhance the task safety by guiding the expansion of the path towards the safest configurations. Our safety notion consists of avoiding dangerous situations, e.g. being very close to the obstacles, human awareness, e.g. being as much as possible in the human vision field, as well as ensuring human safety by being as far as possible from human with hierarchical priority between human body parts. Experimental validations are conducted in simulation and on the real Baxter research robot. They revealed the efficiency of the proposed method, mainly in the case of a collaborative robot sharing the workspace with humans.

The flexibility of the robot assembly process is critical, and a robot assembly system that is not flexible may damage the workpieces. Most researchers make the assembly process flexible by installing a six-dimensional force/torque sensor at the end of robots, but doing so will result in an increase in the costs of the robotic assembly system. To this end, this paper proposes an external force/torque calculation algorithm based on dynamic model identification to replace the six-dimensional force/torque sensor; the algorithm can reduce the costs while achieving a flexible assembly. In this paper, the impedance model of the environment and the dynamic model of the robot with friction are unified. Based on the unified model, the virtual contact surface is proposed to optimize the assembly. To ensure the accuracy of the assembly, the compliant control method of this paper uses the PD-based position control as the control inner loop and the impedance control as the control outer loop. To verify the accuracy of the compliant control method, a 6-DOF series collaborative robot which is developed in our laboratory is used to complete the peg-in-hole assembly experiment. The experimental results show that the algorithm has good flexibility and positional accuracy.

The assisted assembly of customized products supported by collaborative robots combined with mixed reality devices is the current trend in the Industry 4.0 concept. This article introduces an experimental work cell with the implementation of the assisted assembly process for customized cam switches as a case study. The research is aimed to design a methodology for this complex task with full digitalization and transformation data to digital twin models from all vision systems. Recognition of position and orientation of assembled parts during manual assembly are marked and checked by convolutional neural network (CNN) model. Training of CNN was based on a new approach using virtual training samples with single shot detection and instance segmentation. The trained CNN model was transferred to an embedded artificial processing unit with a high-resolution camera sensor. The embedded device redistributes data with parts detected position and orientation into mixed reality devices and collaborative robot. This approach to assisted assembly using mixed reality, collaborative robot, vision systems, and CNN models can significantly decrease assembly and training time in real production.

In the past few years, collaborative robots (i.e., cobots) have been largely adopted within industrial manufacturing. Although robots can support companies and workers in carrying out complex activities and improving productivity, human factors related to cobot operators have not yet been thoroughly investigated. The present study aims to understand the subjective experience of younger and senior workers interacting with an industrial collaborative robot. Results show that workers' acceptance of cobots is high, regardless of age and control modality used. Interesting differences between seniors and younger adults emerged in the evaluations of user experience, usability, and perceived workload of participants and are detailed and commented in the last part of the work.

Manufacturing processes and industrial systems gradually change their traditional layouts and configurations, preparing to introduce novel integrated human-robot technologies as collaborative robots and exoskeletons. Whether mass customization of lot size and the production mix discourages the adoption of capital-intensive automation, collaborative robots become affordable and effective and a hotspot of the debate on manufacturing systems. This paper provides a novel support-design framework for the cooperative robot system in labor-intensive manufacturing processes to aid layout and task scheduling design. Through an iterative closed-loop methodology, this framework explores the impact of a cooperative robot in a labour-intensive manufacturing system like the production facility of a food service company. The framework leads the designer through the re-layout of the end-of-line, the economic and technical feasibility analyses, using simulation to estimate payback and ergonomics benefits for workers. Within the proposed layout, we state that adopting a cooperative cobot for the end-of-line is affordable and ergonomically convenient without representing a safety threat for workers. The testbed confirms the framework as an enabling tool for human-robot technologies integration in current manufacturing systems under budget and workers-driven constraints.

International audience; Human-Robot Interaction (HRI) is a largely ad-dressed subject today. Collision avoidance is one of main strategies that allow space sharing and interaction without contact between human and robot. It is thus usual to use a 3D depth camera sensor which may involves issues related to occluded robot in camera view. While several works overcame this issue by applying infinite depth principle or increasing the number of cameras, we developed in the current work a new and an original approach based on the combination of a 3D depth sensor (Microsoft® Kinect V2) and the proprioceptive robot position sensors. This method uses a principle of limited safety contour around the obstacle to dynamically estimate the robot-obstacle distance, and then generate the repulsive force that controls the robot. For validation, our approach is applied in real time to avoid collision between dynamical obstacles (humans or objects) and the end-effector of a real 7-dof Kuka LBR iiwa collaborative robot.Several strategies based on distancing and its combination with dodging were tested. Results have shown a reactive and efficient collision avoidance, by ensuring a minimum obstacle-robot distance (of ≈ 240mm), even when the robot is in an occluded zone in the Kinect camera view.

International audience; In this paper we present an autonomous camera holder robotic system for minimally invasive surgery (MIS). The proposed system is composed of a 7-DoF collaborative robot, i.e. Franka robot, holding the surgical camera and a motion capture system, i.e. Qualisys system, tracking online the surgical tools movements. The robot adapts its movements to continuously monitor the surgical gestures, based on the tools tips coordinates provided by the Qualisys system. The surgical camera is inserted into the patient’s body through a surgical device, i.e. trocar, generating a kinematic constraint commonly known as Remote Center of Motion (RCM) constraint. In order to preserve the patient safety, the RCM constraint is guaranteed by the control approach. Moreover, a compliance control law is implemented to smooth the robot movements as well as to reduce the efforts generated by the human-robot interactions. Robot Operating System (ROS) framework has been used to establish the communication between the robot and Qualisys, using the UDP protocol for data exchange.

Objective: The application of bubble-based ablation with the focus ultrasound therapy histotripsy is gaining traction for the treatment of venous thrombosis, among other pathologies. For extensive clot burden, the histotripsy source must be translated to ensure uniform bubble activity throughout the vascular obstruction. The purpose of this study was to evaluate the targeting accuracy of a histotripsy system comprised of a focused source, ultrasound image guidance, and a collaborative robot (cobot) positioner. The system was designed with a primary emphasis for treating deep vein thrombosis. Methods: Studies to test treatment planning and targeting bubble activity with the histotripsy-cobot system were conducted in an in vitro clot model. A tissue-mimicking phantom was also targeted with the system, and the predicted and actual areas of liquefaction were compared to gauge the spatial accuracy of ablation. Results: The system provided submillimeter accuracy for both tracking along an intended path (within 0.6 mm of a model vessel) and targeting bubble activity within the venous clot model (0.7 mm from the center of the clot). Good correlation was observed between the planned and actual liquefaction locations in the tissue phantom, with an average Dice similarity coefficient of 77.8%, and average Hausdorff distance of 1.6 mm. Conclusion: Cobots provide an effective means to apply histotripsy pulses over a treatment volume, with the ablation precision contingent on the quality of image guidance. Significance: Overall, these results demonstrate cobots can be used to guide histotripsy ablation for targets that extend beyond the natural focus of the transducer.

Robot dynamics and its parameter identification are of great significance to the realization of optimal control and human&ndash, machine interaction. The objective of this research is to address the shortcomings of establishing and identifying the self-developed six-degree-of-freedom (6-DoF) collaborative robot dynamics, which leads to a large error in the predicted torque of the proposed robot. A long short-term memory (LSTM) in an optimized recurrent neural network (RNN) is proposed to compensate the dynamic model of the proposed 6-DoF collaborative robot based on the consideration of gravity, Coriolis force, inertial force, and friction force. The analysis and experimental findings provide promising results. The compensated collaborative robot dynamic model based on LSTM in an optimized RNN displays a good prediction on the actual torque, and the root-mean-square (RMS) error between predicted and actual torques are reduced by 61.8% to 78.9% compared to the traditional dynamic model. Results of the experimental applications demonstrate the validity of the proposed systematic error compensation strategy.

In this analysis, we present results from measurements performed to determine the stability of a hand tracking system and the accuracy of the detected palm and finger's position. Measurements were performed for the evaluation of the sensor for an application in an industrial robot-assisted assembly scenario. Human-robot interaction is a relevant topic in collaborative robotics. Intuitive and straightforward control tools for robot navigation and program flow control are essential for effective utilisation in production scenarios without unnecessary slowdowns caused by the operator. For the hand tracking and gesture-based control, it is necessary to know the sensor's accuracy. For gesture recognition with a moving target, the sensor must provide stable tracking results. This paper evaluates the sensor's real-world performance by measuring the localisation deviations of the hand being tracked as it moves in the workspace. Web of Science 20 15 art. no. 4088

[EN] Due to the elasticity of their joints, collaborative robots are seldom used in applications with force control. Besides, the industrial robot controllers are closed and do not allow the user to access the motor torques and other parameters, hindering the possibility of carrying out a customized control. A good alternative to achieve a custom force control is sending the output of the force regulator to the robot controller through motion commands (inner/outer loop control). There are different types of motion commands (e.g., position or velocity). They may be implemented in different ways (Jacobian inverse vs. Jacobian transpose), but this information is usually not available for the user. This article is dedicated to the analysis of the effect of different inner loops and their combination with several external controllers. Two of the most determinant factors found are the type of the inner loop and the stiffness matrix. The theoretical deductions have been experimentally verified on a collaborative robot UR3, allowing us to choose the best behaviour in a polishing operation according to pre-established criteria., The authors are grateful for the financial support of the Spanish Ministry of Economy and European Union, grant DPI2016-81002-R (AEI/FEDER, UE), to the research work here published. Rodrigo Perez-Ubeda is grateful to the Ph.D. Grant CONICYT PFCHA/DOCTORADO BECAS CHILE/2017-72180157.

IEEE ICRA Best Paper Award in Automation; International audience; In this work, a robotic assistance strategy is developed to improve the safety in an artisanal task that involves a strong interaction between a machine-tool and an operator. Wood milling is chosen as a pilot task due to its importance in carpentry and its accidentogenic aspect. A physical model of the tooling process including a human is proposed and a simulator is thereafter developed to better understand situations that are dangerous for the craftsman. This simulator is validated with experiments on three subjects using an harmless mock-up. This validation shows the pertinence of the proposed control approach for the collaborative robot used to increase the safety of the task.

Gamybinės įmonės darbuotojų gerovė darbuotojų – robotų sąveikos kontekste yra aktuali tyrimo tema, kadangi visuomenė išgyvena skaitmeninės transformacijos laikotarpį, kurio metu robotų paklausa ir paplitimas auga, jie evoliucionuojasi iš tradicinio pramoninio roboto į bendradarbiaujantį roboto tipą, kas rodo, kad darbuotojai darbo vietoje vis dažniau susiduria su robotais. Šalia to, darbuotojų gerovės tyrimai vykdomi įvairiose srityse, tačiau darbuotojų gerovė darbuotojų – robotų sąveikos kontekste yra pakankamai naujas tyrimo laukas, reikalaujantis naujų tyrimų. Tyrimo objektas: gamybinės įmonės darbuotojų gerovė darbuotojų – robotų sąveikos kontekste. Darbo tikslas: atskleisti gamybinės įmonės darbuotojų gerovę darbuotojų – robotų sąveikos kontekste. Pasirinktas kokybinis tyrimo metodas – interviu, o duomenys analizuojami naudojant aprašomosios fenomenologinės analizės metodą. Atliekant gamybinės įmonės darbuotojų gerovės darbuotojų – robotų sąveikos kontekste tyrimą, išryškėjo 5 pagrindinės rezultatų grupės: darbuotojų gerovė, darbuotojų gerovę formuojantys veiksniai, darbuotojų antigerovė, darbuotojų antigerovę formuojantys veiksniai, tyrimo kontekstas. Tyrimo metu paaiškėjo, kad tiriamoje oragnizacijoje išryškėjo visos gerovės dimensijos. Projekte pateikiamos rekomendacijos organizacijai darbuotojų gerovės lygio didinimui. Kalbant apie ateities tyrimus gamybinės įmonės darbuotojų gerovės darbuotojų – robotų sąveikos kontekste tema, svarbūs tolimensni tyrimai, kuriuos naudinga būtų atlikti kitokio tipo gamybinėje įmonėje (pavyzdžiui, medienos ar maisto pramonės). Taip pat naudinga būtų atlikti kiekybinį tyrimą, kurio metu būtų apskaičiuotas problemos stiprumas ir gylis, o ne tik iškeltos egzistuojančios problemos., The well-being of manufacturing company employees in the context of employee-robot interaction is a relevant research topic as society goes through a period of digital transformation. During this period the demand and prevalence of robots grows, and robots themselves are evolving from a traditional industrial robot to a collaborative type robot, indicating the increase of employees facing robots in the workplace. In addition, research on employee well-being is carried out in various fields, but employee well-being in the context of employee-robot interaction is a relatively new field of research that requires new analysis. The object of the research: the well-being of manufacturing company employees in the context of employee-robot interaction. The aim of the work: to reveal the well-being of the employees of the manufacturing company in the context of employee-robot interaction. The chosen qualitative research method is an interview, and the data are analyzed using the method of phenomenological analysis. The study of the well-being of employees of a manufacturing company in the context of employee-robot interaction revealed 5 main groups of results: employee well-being, factors shaping employee well-being, employee anti-well-being, factors shaping employee anti-wellbeing, research context. The study revealed that all dimensions of well-being became apparent in the organization under study. The project provides recommendations on how organization can increase the level of employee well-being. Regarding the future research on the well-being of manufacturing company employees in the context of employee-robot interaction, further research is important, and it would be useful to conduct it in another type of manufacturing plant (for example, wood or food industry). It would also be beneficial to carry out a quantitative study to calculate the strength and depth of the problem, rather than just to raise existing problems.

[ES] El personal de enfermería y otros trabajadores de los centros hospitalarios emplean una considerable cantidad de tiempo buscando equipamiento y material y transportándolo de un lugar a otro. Resulta muy conveniente maximizar el tiempo dedicado al cuidado de pacientes, ya que repercutiría tanto en una reducción de los costes como en un aumento de la calidad de los servicios sanitarios. Se propone una solución basada en el uso de robots colaborativos. Los robots colaborativos están diseñados con el propósito de compartir su espacio de trabajo con humanos, lo que los hace adecuados para ser introducidos en el sector sanitario. Con el adecuado etiquetado y distribución de materiales y equipamiento en el almacén de un hospital, un robot móvil equipado con un brazo de 7 grados de libertad, sensor lidar y cámara estéreo es capaz de navegar por pasillos y habitaciones a la vez que transporta objetos de un punto a otro del hospital. En la programación del robot, se implementan algoritmos para evitar y comprobar colisiones y para planificación de rutas; así como algoritmos de visión artificial para la correcta identificación de los objetos manipulados., [EN] Nursing staff and other hospital workers spend a significant portion of their time looking for equipment and materials and moving them from one place to another. It is highly desirable that the amount of time spent in patient care is maximized, as it would both reduce costs and improve healthcare quality. A solution based on the use of collaborative robots is proposed. Collaborative robots are designed with the intent of sharing their workspace alongside humans, which makes them suitable for being introduced in a healthcare environment. With appropriate labelling and distribution of materials and equipment inside an hospital storage facility, a mobile robot equipped with a 7-DOF robotic arm, lidar sensor and stereo camera can successfully navigate corridors and rooms while transporting items from one point of the hospital to another. Collision avoidance, collision checker and motion planning algorithms are implemented in the robot s programming; as well as machine vision algorithms for identifying the handled objects.

Collaborative robots are among the key enabling technologies of the fourth industrial revolution and have the potential to change the way people and machines physically interact. Such collaborative robotics applications can be successful in small- and medium-sized enterprises (SMEs) only if they are properly implemented, taking into account safety and ergonomics of the shared workplace. This chapter first reviews safety standards, methods for risk assessment, and the concept of ergonomics of workplaces. The chapter discusses why collaborative robotics can be seen as important potential for SMEs and what the challenges are that SMEs are facing when implementing collaborative workspaces in the company. In conclusion, the chapter gives recommendations for future topics of research to overcome the barrier to introducing smart automation in SMEs.

The robotic arms of the human arm type, so-called collaborative robots, have been improved, optimized, and diversified greatly in recent years. However, most of them are still equipped with mechanical grippers with plier-like jaws. Equipping these robotic arms with anthropomorphic grippers is currently hampered by variants of these grippers on the market that are far too complex and at inaccessible prices to be used on a large scale. As an alternative to the familiar anthropomorphic grippers, I presented an anthropomorphic gripper with five fingers, made under my coordination, constructive, and functional, including briefly the coupling solution with a robotic arm.

Industrial robots have served industry for decades, especially the automotive industry. The traditional industrial robotics have shown their limits in task management due to the rigid and time-consuming programming and task planning. In recent years, to achieve the Industry 4 transformation, a broad range of collaborative robots (cobots) have been employed for autonomously executing tasks in different domains. Cobots, mainly used in manufacturing, were extensively developed, and integrated into real production contexts to optimise processes and improve productivity. However, motion control and programming for cobots remain an obstacle to achieve their potential as the procedure still takes time and disrupts processes. This paper critically reviews current mainstream control methods for industrial robotics to execute tasks and proposes an approach for rapid task re-planning for cobots in a flexible assembly workcell. The proposed method allows cobots to execute flexible assembly tasks for small batch production/assembly, or even single products and to re-plan the new task without interruption. Its advantages and limitations are also discussed Refereed/Peer-reviewed

The article deals with possibilities of using of a two-handed collaborative robot in automated production. The introductory part of this paper is about robot manufacturers' proposed ways of use of collaborative robots and a consideration of correctness of this stance. In this matter, an alternative point of view is proposed and tested, where a collaborative robot does not cooperate with a worker but replaces him/her completely. The main part of the study focuses on a specific installation of the YuMi collaborative robot into an already existing production line of a leading Czech supplier in the automotive industry. This real application is verified in simulations with an alternative solution consisting of two traditional industrial robots ABB IRB 120 instead. These data are evaluated and the advantages of deploying the collaborative robot and the industrial robots in the specific assembly application are compared. Economic return and productivity in high production cycle applications are considered. The article then describes the difficulties caused by the low load capacity of the YuMi collaborative robot and an alternative approach using the FEM methodology and topology optimization in the robot grip jaws design. Web of Science 60 2 157 151

Primjenom Industrije 4.0 moderniziraju se proizvodni procesi u industriji, ali se pri tome mora voditi računa o sigurnosti radnika. Automatizacija proizvodnih procesa i podizanje na višu razinu može se ostvariti primjenom kolaborativnih robota koji rade skupa s radnicima, a što se tiče sigurnosti radnika zajamčena je njihova sigurnost tako da nema ozljeda pri radu. Primjenom kolaborativnih robota koriste se sve prednosti koje oni imaju nad industrijskim robotima prve generacije kao što su: zajedno rade s radnicima, radnici rade u sigurnom okruženju, zauzimaju manje prostora, robote nije porebno ogradama odvajati od radnika, jednostavni su za manipulaciju, jeftiniji su, mogućnost primjene u malim i srednjim kompanijama, moguće raznerazine automatizacije u proizvodnom procesu, pri čemu se zadatci mogu djelomično automatizirati u onim slučajevima kada je potpuna automatizacija suviše kompleksna ili nije ekonomična. Trend primjene kolaborativnih robota u budućnosti će imati rastući karakter, jer ciljeve četvrte industrijske revolucije nije moguće postići bez kolaborativnih robota, drugim riječima doći će do “pametnih proizvodnih procesa” odnosno “pametnih tvornica”., By applying Industry 4.0, modernization of the production processes in industry is achieved. However, the safety of workers must be a priority. Automation of production processes and raising it to a higher level can be achieved by employing collaborative robots working together with workers. The degree of safety measures guarantees that there are no work injuries. In using collaborative robots we exploit all the advantages that they possess over first-generation industrial robots. They work together with workers, workers work in a safe environment, robots take up less space, they are not physically separated from workers, they are easy to manipulate, they are cheaper, and are suitable for small and medium size companies. We have the possibility of introducing different levels of automation in the production process, i.e. we can partially automate the tasks where complete automation is too complex or not economical. The use of collaborative robots will grow in the future, since the goals of the fourth industrial revolution cannot be achieved without collaborative robots, in other words, without the "smart manufacturing process" or "smart factory".

The main topic of this paper is concentrated on collaborative robots. Specifically preparation of their implementation in terms of safety requirements specification in the Czech Republic. Firstly, the paper is concentrated on a description of collaborative robots, their advantages and disadvantages. Then the main subject of the paper is described in the analysis of the safety requirements in relation to the legislative conditions of the Czech Republic. Not respecting the safety requirements can have significant consequences for a company implementing collaborative robots. The paper describes three important parts of the safety requirements: technical standards related to machines, legislative machinery regulations and technical standards related to industrial robots and collaborative robots. The important parts of the safety requirements are mentioned specifically with references.

The research reported in this paper proposes a new approach to collaborative robots that aims at improving the simplicity and efficiency of the programming task for non-technical users. It is grounded on three standpoints: (i) an elementary and disciplined paradigm for robot programming, called the simple programming journey, (ii) a hybrid interaction mode where robot tasks can be programmed using a natural language chat and, if necessary, can be completed and finalized through a block-based interface, and (iii) a robust cognitive match between the mental models of the user and the programming interface. The proposed approach has been implemented and tested through the development of a prototype programming environment called CAPIRCI, which can be tailored to different application domains through the definition of objects, locations, and actions. CAPIRCI has been tested by real users with a COBOTTA robot by DENSO WAVE Ltd. Two experimental tests have been carried out in order to validate the novel approach proposed and to assess its impact on end-user programming. The results obtained show that a hybrid approach exploiting both natural language dialogue and block-based interaction can help make the programming task easy and efficient for non-technical users.

The first part of this paper firstly theoretically presents first three industrial revolutions, main inventions and their impact on society and industry development. Then, Industry 4.0 is presented with focus on use of collaborative robots and their role is highlighted. Main part of the article focuses on the Laboratory of Industry 4.0 at University of West Bohemia, its key components, use in education and future plans.

Recent developments in robotics have resulted in implementations that have drastically increased collaborative interactions between robots and humans. As robots have the potential to collide intentionally and/or unexpectedly with a human during the collaboration, effective measures to ensure human safety must be devised. In order to estimate the collision safety of a robot, this study proposes a virtual sensor based on an analytical contact model that accurately estimates the peak collision force and pressure as the robot moves along a pre-defined path, even before the occurrence of a collision event, with a short computation time. The estimated physical interaction values that would be caused by the (hypothetical) collision were compared to the collision safety thresholds provided within ISO/TS 15066 to evaluate the safety of the operation. In this virtual collision sensor model, the nonlinear physical characteristics and the effect of the contact surface shape were included to assure the reliability of the prediction. To verify the effectiveness of the virtual sensor model, the force and pressure estimated by the model were compared with various experimental results and the numerical results obtained from a finite element simulation.

To protect operators and conform to safety standards for human&ndash, machine interactions, the design of collaborative robot arms often incorporates flexible mechanisms and force sensors to detect and absorb external impact forces. However, this approach increases production costs, making the introduction of such robot arms into low-cost service applications difficult. This study proposes a low-cost, sensorless rigid robot arm design that employs a virtual force sensor and stiffness control to enable the safety collision detection and low-precision force control of robot arms. In this design, when a robot arm is subjected to an external force while in motion, the contact force observer estimates the external torques on each joint according to the motor electric current and calculation errors of the system model, which are then used to estimate the external contact force exerted on the robot arm&rsquo, s end-effector. Additionally, a torque saturation limiter is added to the servo drive for each axis to enable the real-time adjustment of joint torque output according to the estimated external force, regulation of system stiffness, and achievement of impedance control that can be applied in safety measures and force control. The design this study developed is a departure from the conventional multisensor flexible mechanism approach. Moreover, it is a low-cost and sensorless design that relies on model-based control for stiffness regulation, thereby improving the safety and force control in robot arm applications.

In this paper, we present non-photorealistic rendering techniques that are applied together with a painting robot to realize artworks with original styles. Our robotic painting system is called Busker Robot and it has been considered of interest in recent art fairs and international exhibitions. It consists of a six degree-of-freedom collaborative robot and a series of image processing and path planning algorithms. In particular, here, two different rendering techniques are presented and a description of the experimental set-up is carried out. Finally, the experimental results are discussed by analyzing the elements that can account for the aesthetic appreciation of the artworks.

Hospitals are crucial aspects of society, run by incredible people that dedicate their life to caring for others. However, there are several tasks that are vital to a hospitals operation that do not require an empathic competence. One such tasks is the continuous resupply of consumable items needed to maintain necessary hygiene levels. The Pluto concept act as a helping hand to the assistant nurses, relieving them and enabling them to spend more time with the patients and emphasizes their empathic, inherently human capabilities. The chief motivation is that nurses value the interaction with the patients the most in their work, which is also their primary task. However, they are charged with so many menial tasks that they have little time to care for their patients.

Skapat av Högskolan i Skövde och på uppdrag av Elektroautomatik i Skövde har detta projekt genomförts för att identifiera möjliga människa-robot samarbeten i monteringsmiljö. Robotarna som funnits i åtanke för denna form av samarbete är kollaborativa robotar. I dagens industri existerar redan kollaborativa robotar men utför ofta uppgifter på en mer samexisterande nivå avskild från människan. Den form av människa-robot samarbete som undersökts i detta arbete är där båda parter assisterar varandra i en arbetsuppgift på gemensam yta. Detta koncept har blivit allt viktigare för dagens företag som efterfrågar ett mer flexibelt och anpassningsbart system i framtiden. Under projektet undersöktes även förbättringsförslag på nuvarande lösningar för kollaborativa robotar samt processen kring robotlösningen. Genom studerad litteratur utformades tre intervjuprotokoll avsedda för en intervjustudie med tre olika yrkesgrupper – montörer, produktionstekniker och ingenjörer. Intervjustudien utfördes i samarbete med företag i Skövde där kunskap extraherats från personer inom monteringsmiljö. Kärnfrågan i samtliga intervjuprotokoll var i vilka uppgifter i monteringsmiljö som intervjupersonen såg möjlighet till ett människa-robot samarbete. Insamlad data har transkriberats, strukturerats och sorterats för att kunna sammanställa ett resultat. Förslag på möjliga arbetsmoment som framkom under intervjustudien delades in i sex kategorier: Svåråtkomligt, tidskrävande, ergonomisk avlastning, logistik, kvalitet och produktvariation. Ett resultat presenteras där samarbetsuppgifter mellan människa och robot sammanställts från intervjustudien. Dessa har sorterats efter de sex kategorierna inom möjliga arbetsmoment. Övergripande förslag angavs under intervjustudien på vilken typ av uppgifter och områden en kollaborativ robot hade kunnat samarbeta med en människa. Dessa förslag föll under flera kategorier – exempelvis äntring av stort antal skruvar vilket kan kategoriseras enligt både ergonomisk avlastning och tidskrävande. Den kategori som genererat flest förslag är arbetsuppgifter där en kollaborativ robot kan erbjuda ergonomisk avlastning för människan. För att identifiera mer specifika arbetsuppgifter behöver ytterligare undersökning utföras baserat på de områden som identifierats i detta arbete. Den kollaborativa robotlösningen behöver kunna arbeta inom flera olika kategorier för att uppnå den framtida flexibla produktion som efterfrågas. Created by the University of Skövde and assigned by Elektroautomatik in Skövde this project was executed to identify possible HRC tasks in the assembly industry. The robots that were reviewed for this type of collaboration tasks were collaborative robots. Collaborative robots already exists in today’s industry but are commonly working on a co-existing level separated from the human. The type of collaboration investigated during this project regards solving tasks where the human and robot assist each other on a common work surface. This concept has gained more importance for companies today because of the increasing demand of a more flexible and adaptable system for the future production. Improvement proposals has been generated during the project regarding the collaborative robot and its implementation process. Based on the researched literature three interview protocols was created for three different groups of professions – assemblers, production technicians and engineers. In collaboration with companies in Skövde the interviews were executed gathering knowledge from people working within the assembly environment. The main question in all interview protocols were in which type of assembly tasks the interviewed could see a possibility for HRC. Collected data has been transcribed, structured and sorted in order to reach a result. Proposals of possible HRC operations gathered from the interviews were divided into six categories – inaccessible, time demanding, ergonomic relief, logistics, quality and product variety. A result has been presented where HRC tasks has been compiled from the interviews. These has been sorted into the six categories generated from possible HRC operations. General ideas were proposed during the interviews regarding what possible type of tasks and areas a collaborative robot could work together with a human. In many cases the proposals given could be sorted into more than one category – for example assemble of a large amount of screws that could be categorized as both ergonomic relief and time demanding. The category that generated the largest amount of proposals of HRC were tasks intended to offer ergonomic relief for the human. To identify more specific HRC tasks further research need to be performed based on the categories of areas that has been identified in this project. The future collaborative robot solution has to be able to combine more than one category to reach the flexible and adaptable system that is demanded.

International audience; Human Robot Collaboration is seen as a significant feature of Industry 4.0 implementation. Collaborative robots (cobots) are supposed to deliver superior process performance, which was so far achieved through the application of Lean Manufacturing techniques. The following case study built around the assembly process of a pneumatic cylinder, tends to analyse not only the actual benefits of cobot implementation, but also the success factors, in conjunction with Lean Manufacturing usage. Finally, this paper suggests a draft method towards the successful integration of cobot.

Aiming at the characteristics of high efficiency and smoothness in the motion process of collaborative robot, a multi-objective trajectory planning method is proposed. Firstly, the kinematics model of the collaborative robot is established, and the trajectory in the workspace is converted into joint space trajectory using inverse kinematics method. Secondly, seven-order B-spline functions are used to construct joint trajectory sequences to ensure the continuous position, velocity, acceleration and jerk of each joint. Then, the trajectory competitive multi-objective particle swarm optimization (TCMOPSO) algorithm is proposed to search the Pareto optimal solutions set of the robot&rsquo, s time-energy-jerk optimal trajectory. Further, the normalized weight function is proposed to select the appropriate solution. Finally, the algorithm simulation experiment is completed in MATLAB, and the robot control experiment is completed using the Robot Operating System (ROS). The experimental results show that the method can achieve effective multi-objective optimization, the appropriate optimal trajectory can be obtained according to the actual requirements, and the collaborative robot is actually operating well.

International audience; This paper presents a study on the impact of autonomy in the context of human-robot collaboration. We consider two conditions: i) a semi-autonomous robot that decides when to execute a supporting action, and ii) a support robot that has to be instructed of each action on a collaborative task. The semi-autonomous robot gradually learns how to support the human through experience. We found that users prefer the semi-autonomous robot and that the behavior was closer to their expectations despite them being more afraid of it. We also found that even if users noticed the robot was learning in one case, they wanted more autonomy in both conditions.

In lean production environments, such as the U-shaped cells, flexibility is a priority. Therefore, any element that introduces process stiffness is negatively valued. Former studies establish that robotization of tasks in U-shaped cells presents some drawbacks. For instance: it may complicate continuous improvement, prolong changeover time, use a large space or create safety problems for the operators. However, the collaborative robots (CoBots) may change this situation, since they overcome most of the issues previously mentioned. The present study analyses a real case of de-robotization in a traditional assembly line to transform it into a manual U-shaped line. In a second step a CoBot is integrated in the cell replacing one of the workers. This study empirically compares the manufacturing process in these three scenarios. Results in real production conditions show that a U-shape cell assisted by a CoBot increases productivity and reliability while reducing the surface used. These results suggest that collaborative robotics can be integrated in U-shaped production lines and even increase the efficiency of a traditional robotized assembly line.

Purpose – The paper aims to deliver an approach of how lightweight robot systems can be used to automate manual processes for higher efficiency, increased process capability and enhanced ergonomics. To show how these systems can be utilized in practice, a new collaborative testing system for an automated water leak test was designed using an image processing system utilized by the robot. Design/methodology/approach – 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 optimizes 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 optimization allows the collaboration of robots and manual labour which, in turn, enhances the capability of the process station. Findings – This paper examines the development of novel applications for lightweight robotic systems and provides a suitable process whereby the systems are optimized in technical, ergonomic and safety-related aspects. Research limitations/implications – A new automated testing process in combination with a processing algorithm was developed. Practical implications – To optimize and validate the system, it was set up in a true to reality model factory and brought to a prototypical status. Several original equipment manufacturers showed great interest in implementing the system in their assembly line. Social implications – The direct human–robot collaboration allows humans and robots to share the same workspace without strict separation measures which is a great advantage compared with traditional industrial robots. The workers benefit from a more ergonomic workflow and are relieved from unpleasant, repetitive and burdensome tasks. Originality/value – A lightweight robotic system was implemented in a continuous assembly line as a new area of application for these systems. The automated water leak test gives a practical example of how to enrich the assembly and commissioning lines, which are currently dominated by manual labour, with new technologies. This is necessary to reach a higher efficiency and process capability while maintaining a higher flexibility potential than fully automated systems.