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Warehouse operations have been significantly improved because of the rapid advancement of cyber-physical system technologies, preparing for Work-of-the-Future. The challenge, however, is how to design a collaborative system to deliver optimal performance by multiple agents who are highly distributed but interconnected and operate with technologies that provide massive amounts of real-time data. To address the challenge, in this article, the Cyber Collaborative Protocol for Dual-Cycle Task in Future Warehouse is developed to minimise total operation cost and time. The problem is addressed in two phases; the Global and Local phases. The global phase has higher computational power, maintaining a mathematical model, while the local phase has limited computational power and time, utilising heuristics to deliver the outcome. Computer experiments are utilised for validating the designed protocol compared with other alternatives. The results show that, in all given scenarios, the newly designed protocol outperforms alternatives with statistical significance. The original contribution of this research is the design and control of Cyber Collaborative Warehouse operations with a new focus on collaborative multi-agent interactions. In addition, a major implication is that future warehouses can benefit competitively by operating with Task Administration Protocols such as the new Cyber Collaborative Protocol for Dual-Cycle Task in Future Warehouse. [ABSTRACT FROM AUTHOR]

Cooperative robots that perform safety functions as part of cooperative work with humans have been recently drawing attention. Proximity and tactile sensors that can be retrofitted to a robot's surface are important safety measures for existing robots that are not manufactured as cooperative robots to be used as cooperative robots. In this paper, a string‐like self‐capacitance‐based proximity and tactile sensor that can be easily wrapped around various types of existing robots is proposed. The novel and useful point in this paper is that it can be easily mounted on various robots by a flexible string‐like proximity and tactile sensor. The sensor module can be adjusted to the required length by connecting different numbers of modules depending on the mounting surface. As a demonstration, six prototype sensor modules were connected by each connector and wrapped around a robotic arm. The sensor modules on the robot's surface could detect an object within its proximity range and detect the rough pressure after contact. In addition, the robotic arm with the sensor modules could be controlled in real time using the data obtained from the sensor that are object detection data at proximity range. These results confirm that the proposed sensor module can be used in the proximity and tactile sensors of existing robots. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The article presents the possibilities of automating production pre-processing and post-processing operations for the Material Extrusion - MEX process based on Fused Filament Fabrication technology. Automation is based on hardware and software solutions. For this purpose, a special research station was developed, equipped with a warehouse of working platforms, a 3D printer and a collaborative robot that integrates individual elements of the manufacturing process. The developed solution allows for increasing the efficiency of the manufacturing cell and reducing the operator's involvement in manual operations at the pre-processing and post-processing stages. [ABSTRACT FROM AUTHOR]

This paper proposes a method for solving the path planning problem for a collaborative robot. The time-optimal, smooth, collision-free B-spline path is obtained by the application of a nature-inspired optimization algorithm. The proposed approach can be especially useful when moving items that are delicate or contain a liquid in an open container using a robotic arm. The goal of the optimization is to obtain the shortest execution time of the production cycle, taking into account the velocity, velocity and jerk limits, and the derivative continuity of the final trajectory. For this purpose, the velocity profiling algorithm for B-spline paths is proposed. The methodology has been applied to the production cycle optimization of the pick-and-place process using a collaborative robot. In comparison with point-to-point movement and the solution provided by the RRT* algorithm with the same velocity profiling to ensure the same motion limitations, the proposed path planning algorithm decreased the entire production cycle time by 11.28% and 57.5%, respectively. The obtained results have been examined in a simulation with the entire production cycle visualization. Moreover, the smoothness of the movement of the robotic arm has been validated experimentally using a robotic arm. [ABSTRACT FROM AUTHOR]

This study investigates the potential of a voice-controlled collaborative robot to promote computational thinking (CT) skills in preschoolers aged 4 to 6 in Southern Chile. During a week-long workshop, 34 children engaged in activities designed to develop several CT components while interacting with a robotic arm. Pre- and post-workshop assessments utilizing the TechCheck-K tool revealed significant improvements in CT skills. The findings of this preliminary study demonstrate the effectiveness of voice-controlled robots as innovative tools in early education, significantly enhancing young learners' understanding of CT concepts, practices, and perspectives. This research advocates for further exploration of robotic integration in educational settings, highlighting their potential to improve or extend preschool learning environments and foster CT skill development. [ABSTRACT FROM AUTHOR]

Objective: This study investigated the effects of different approach directions, movement speeds, and trajectories of a co-robot's end-effector on workers' mental stress during handover tasks. Background: Human–robot collaboration (HRC) is gaining attention in industry and academia. Understanding robot-related factors causing mental stress is crucial for designing collaborative tasks that minimize workers' stress. Methods: Mental stress in HRC tasks was measured subjectively through self-reports and objectively through galvanic skin response (GSR) and electromyography (EMG). Robot-related factors including approach direction, movement speed, and trajectory were analyzed. Results: Movement speed and approach direction had significant effects on subjective ratings, EMG, and GSR. High-speed and approaching from one side consistently resulted in higher fear, lower comfort, and predictability, as well as increased EMG and GSR signals, indicating higher mental stress. Movement trajectory affected GSR, with the sudden stop condition eliciting a stronger response compared to the constrained trajectory. Interaction effects between speed and approach direction were observed for "surprise" and "predictability" subjective ratings. At high speed, approach direction did not significantly differ, but at low speeds, approaching from the side was found to be more surprising and unpredictable compared to approaching from the front. Conclusion: The mental stress of workers during HRC is lower when the robot's end effector (1) approaches a worker within the worker's field of view, (2) approaches at a lower speed, or (3) follows a constrained trajectory. Application: The outcome of this study can serve as a guide to design HRC tasks with a low level of workers' mental stress. [ABSTRACT FROM AUTHOR]

Robots in hazardous environments demand precise and advanced motion control, making extensive simulations crucial for verifying the safety of motion planning. This paper presents a simulation system that enables interactive path editing, allowing for motion planning in a simulated collaborative robot environment and its real-world application. The system includes a simulation host, a control board, and a robot. Unity 3D on a Windows platform provides the simulation environment, while a virtual Linux environment runs ROS2 for execution. Unity sends edited motion paths to ROS2 using the Unity ROS TCP Connector package. The ROS2 MoveIt framework generates trajectories, which are synchronized back to Unity for simulation and real-world validation. To control the six-axis Indy7 collaborative robot, we used the MIO5272 embedded board as an EtherCAT master. Verified trajectories are sent to the target board, synchronizing the robot with the simulation in position and speed. Data are relayed from the host to the MIO5272 using ROS2 and the Data Distribution Service (DDS) to control the robot via EtherCAT communication. The system enables direct simulation and control of various trajectories for robots in hazardous environments. It represents a major advancement by providing safe and optimized trajectories through efficient motion planning and repeated simulations, offering a clear improvement over traditional time-consuming and error-prone teach pendant methods. [ABSTRACT FROM AUTHOR]

Collaborative robots are used in scenarios requiring interaction with humans. In order to improve the safety and adaptability of collaborative robots during human–robot interaction, this paper proposes a modular wire-actuated robotic arm with symmetric variable-stiffness units. The variable-stiffness unit is employed to extend the stiffness-adjustment range of the robotic arm. The variable-stiffness unit is designed based on flexure, featuring a compact and simple structure. The stiffness–force relationship of the variable-stiffness unit can be fitted by a quadratic function with an R-squared value of 0.99981, indicating weak nonlinearity. Based on the kinematics and stiffness analysis of the symmetric joint module of the robotic arm, the orientation of the joint module can be adjusted by regulating the length of the wires and the stiffness of the joint module can be adjusted by regulating the tension of the wires. Because of the actuation redundancy, the orientation and stiffness of the joint module can be adjusted synchronously. Furthermore, a direct method is proposed for the stiffness-oriented wire-tension-distribution problem of the 1-DOF joint module. A simulation is carried out to verify the proposed method. The simulation result shows that the deviation between the calculated stiffness and the desired stiffness was less than 0.005%. [ABSTRACT FROM AUTHOR]

The depth image obtained by consumer-level depth cameras generally has low resolution and missing regions due to the limitations of the depth camera hardware and the method of depth image generation. Despite the fact that many studies have been done on RGB image completion and super-resolution, a key issue with depth images is that there will be evident jagged boundaries and a significant loss of geometric information. To address these issues, we introduce a multi-scale progressive fusion network for depth image completion and super-resolution in this paper, which has an asymptotic structure for integrating hierarchical features in different domains. We employ two separate branches to learn the features of a multi-scale image given a depth image and its corresponding RGB image. The extracted features are then fused into different level features of these two branches using a step-by-step strategy to recreate the final depth image. To confine distinct borders and geometric features, a multi-dimension loss is also designed. Extensive depth completion and super-resolution studies reveal that our proposed method outperforms state-of-the-art methods both qualitatively and quantitatively. The proposed methods are also applied to two human–robot interaction applications, including a remote-controlled robot based on an unmanned ground vehicle (UGV), AR-based toolpath planning, and automatic toolpath extraction. All these experimental results indicate the effectiveness and potential benefits of the proposed methods. [ABSTRACT FROM AUTHOR]

Collaborative robots are an integral component of the intelligent manufacturing field. The recognition of hand motions based on surface electromyography signals is even more significant for advancing the research of collaborative robots. However, supervised learning based hand motions recognition methods require an enormous quantity of data as support and must meet the condition of independent and identical distribution. In real-world scenarios, gender classifications, collecting conditions, and even individual-to-individual variances may influence the data, posing a challenge for the recognition of hand motions from new participants. Consequently, we propose a domain adaptive framework based on subspace and second-order statistical distribution alignment (SSDA) to overcome the issue of non-independently and identically distributed data shift. We combine the second-order statistical distribution alignment and subspace alignment. SSDA diminishes the geometric and statistical distribution discrepancies between the training and test sets in hand motions recognition. SSDA enhances the average accuracy of hand motions recognition by 26.66%, 14.43%, and 25.76% in three cross-domain scenarios (cross-gender, cross-circumstance, and cross-individual), respectively, compared with the baseline method of direct classification. Experimental results indicate that the proposed method is effective in solving the problem of distribution shift between target data (test set) and priori data (training set) in hand motions recognition. Simultaneously, it improves the recognition accuracy of classifier for different distributed data, thereby providing a new idea for achieving efficient human–robot collaboration. [ABSTRACT FROM AUTHOR]

In the era of Industry 4.0, manufacturing enterprises are actively adopting collaborative robots (Cobots) in their productions. Current online and offline robot programming methods are difficult to use and require extensive experience or skills. On the other hand, the manufacturing industries are experiencing a labor shortage. An essential question, therefore, is: how would a new robot programming method help novice users complete complex tasks effectively, efficiently, and intuitively? To answer this question, we proposed HA R 2 bot, a novel human-centered augmented reality programming interface with awareness of cognitive load. Using NASA's system design theory and the cognitive load theory, a set of guidelines for designing an AR-based human-robot interaction system is obtained through a human-centered design process. Based on these guidelines, we designed and implemented a human-in-the-loop workflow with features for cognitive load management. The effectiveness and efficiency of HA R 2 bot are verified in two complex tasks compared with existing online programming methods. We also evaluated HA R 2 bot quantitatively and qualitatively through a user study with 16 participants. According to the user study, compared with existing methods, HA R 2 bot has higher efficiency, a lower overall cognitive load, lower cognitive loads for each type, and higher safety. [ABSTRACT FROM AUTHOR]

Smart factories build on cyber-physical systems as one of the most promising technological concepts. Within smart factories, condition-based and predictive maintenance are key solutions to improve competitiveness by reducing downtimes and increasing the overall equipment effectiveness. Besides, the growing interest towards operation flexibility has pushed companies to introduce novel solutions on the shop floor, leading to install cobots for advanced human-machine collaboration. Despite their reliability, also cobots are subjected to degradation and functional failures may influence their operation, leading to anomalous trajectories. In this context, the literature shows gaps in what concerns a systematic adoption of condition-based and predictive maintenance to monitor and predict the health state of cobots to finally assure their expected performance. This work proposes an approach that leverages on a framework for fault detection and diagnostics of cobots inspired by the Prognostics and Health Management process as a guideline. The goal is to habilitate first-level maintenance, which aims at informing the operator about anomalous trajectories. The framework is enabled by a modular structure consisting of hybrid series modelling of unsupervised Artificial Intelligence algorithms, and it is assessed by inducing three functional failures in a 7-axis collaborative robot used for pick and place operations. The framework demonstrates the capability to accommodate and handle different trajectories while notifying the unhealthy state of cobots. Thanks to its structure, the framework is open to testing and comparing more algorithms in future research to identify the best-in-class in each of the proposed steps given the operational context on the shop floor. [ABSTRACT FROM AUTHOR]

Currently, collaborative robots (cobots) are mostly programmed to do one task repetitively. They can be programmed at different speeds and work near human operators. The goal of our research was to investigate the effect of robot speed on acceptance, subjective and objective stress, and cognitive workload of individuals. Therefore, we organized a repeated measures experiment in which participants (N = 25) conducted an assembly task with the YuMi cobot from ABB at a low and at a high speed. Subjective and physiological responses were collected, and participants were subjected to a standardized stress test. Our results indicate that when working with a cobot at a high speed, people believe they can work faster and be more productive but also experience a higher workload and higher perceived stress. We also found that tonic EDA is a significant physiological predictor for monitoring perceived stress in humans. We observed a greater relative increase in tonic EDA from baseline to task execution during high-speed mode compared to low-speed mode. Additionally, this increase in tonic EDA significantly correlated with participants' perceived stress levels. However, workload could not be predicted by any of the physiological measures. Future research should explore the effect of higher cobot working speeds and the use of physiological measures (such as stress) as input to guide the collaboration between individuals and cobots. [ABSTRACT FROM AUTHOR]

Human–robot collaborative systems bring several benefits in using human and robot capabilities simultaneously. One of the critical questions is the impact of these systems on production process efficiency. The search for high-level efficiency is severely dependent on collaborative robot characteristics and motion parameters, and the ability of humans to adjust to changing circumstances. Therefore, our research analyzes the effect of the changing collaborative robot motion parameters, acoustic parameters and visual factors in a specific assembly operation, where efficiency is measured through operation times. To conduct our study, we designed a digital twin-based model and a laboratory environment experiment in the form of a collaborative workplace. The results show that changing the motion, acoustic and visual parameters of the collaborative workplace impact the assembly process efficiency significantly. [ABSTRACT FROM AUTHOR]

Robot workpiece machining is interesting in industry as it offers some advantages, such as higher flexibility in comparison with the conventional approach based on CNC technology. However, in recent years, we have been facing a strong progressive shift to custom-based manufacturing and low-volume/high-mix production, which require a novel approach to automation via the employment of collaborative robotics. However, collaborative robots feature only limited motion capability to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the workpiece surface constraint in the robot kinematic analysis, which enables an evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot's task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments. [ABSTRACT FROM AUTHOR]

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]

Bio-simulants and finite element (FE) models have been used to investigate internal injuries caused by external impacts. As the collaboration between humans and industrial robots increases, it is important to understand the expected injuries or damage caused by collaborative robots. In this paper, FE models of the human chest were built to investigate injuries caused by low-speed non-penetrating blunt impacts from collaborative robots. The FE models were validated by comparing them with experimental results. The validated FE models were then used to calculate the maximum force and deformation that would be experienced by the human chest under different impact conditions. The results of the FE analysis were compared with relevant real human test studies. [ABSTRACT FROM AUTHOR]

Objective: Trade-offs between productivity, physical workload (PWL), and mental workload (MWL) were studied when integrating collaborative robots (cobots) into existing manual work by optimizing the allocation of tasks. Background: As cobots become more widely introduced in the workplace and their capabilities greatly improved, there is a need to consider how they can best help their human partners. Methods: A theoretical data-driven analysis was conducted using the O*NET Content Model to evaluate 16 selected jobs for associated work context, skills, and constraints. Associated work activities were ranked by potential for substitution by a cobot. PWL and MWL were estimated using variables from the O*Net database that represent variables for the Strain Index and NASA-TLX. An algorithm was developed to optimize work activity assignment to cobots and human workers according to their most suited abilities. Results: Human workload for some jobs decreased while workload for some jobs increased after cobots were reassigned tasks, and residual human capacity was used to perform job activities designated the most important to increase productivity. The human workload for other jobs remained unchanged. Conclusions: The changes in human workload from the introduction of cobots may not always be beneficial for the human worker unless trade-offs are considered. Application : The framework of this study may be applied to existing jobs to identify the relationship between productivity and worker tolerances that integrate cobots into specific tasks. [ABSTRACT FROM AUTHOR]

As a critical component of the joint gearbox, spur gear pairs play a crucial role in energy conversion, limiting the performance of a collaborative robot. Accurately assessing their instantaneous efficiency and torque fluctuation is essential for developing high-precision robot joint control models. This study proposes a computational model to predict the instantaneous efficiency and torque fluctuation of spur gears under typical operating conditions. The model incorporates a torque balance model, a load distribution model, and a friction model to reflect the relationship between gear meshing position and efficiency. The instantaneous efficiency and torque fluctuation of gear pairs were compared with the Coulomb friction model with an average friction coefficient and the elastohydrodynamic lubrication model with a time-varying friction coefficient. The effect of gear contact ratio on efficiency is analysed, while the instantaneous efficiency and torque fluctuation of gears are studied under varying operating conditions. The results indicate a maximum efficiency difference of 1.86 % between the two friction coefficient models. Under specific operating conditions, the instantaneous efficiency variation of the gear pair can reach 3.34 %, and the torque fluctuation can reach 5.19 Nm. Finally, this study demonstrates the effectiveness and accuracy of the proposed method through comparative analysis. [ABSTRACT FROM AUTHOR]

In the 1990's, Robotics began to design a new robot aimed at industries (primarily automotive) that worked and interacted with humans outside the cage, thereby replacing traditional robots for some specific duties. This robot is therefore called co-bot (collaborative and robot). Also in the 1990's, Robotics designed the social robot (for which we propose the neologism so-bot), aimed at assisting humans and keeping them company. The sociality of the sobots lies in their ability to follow the rules of human social life, make decisions independently, and respect the roles assigned to them. Scientific literature usually keeps the terms collaborative and social robot distinct as if they indicated different and separate concepts. We question this separation and affirm that to collaborate (from the Latin cum-laboro) means to interact with someone while respecting their nature. Collaboration is that particular form of sociality that relates to work activity. From this it follows that the cobot is essentially social and that cobots and sobots belong to the same category that we call co-s-bots (collaborative social robots). In other words, cobots and sobots are two types of cosbots, as the flea and the elephant are two types of animals. The difference between cobot and sobot is given by the development of AI. Both are potentially social, that is, potentially capable of interacting and making decisions independently; but while the cobot is social in potency, the sobot is social 'in act'. With Aristotelian terminology we can therefore say that the cobot is a sobot in power, while the sobot is a cobot in act. We call this new concept 'cobot ontology'. Such an ontology makes it possible to classify cobots according to the degree of development of AI, just as living beings are classified according to the level of intelligence developed.To teach the cosbot to interact with humans, engineers use some results of neuroscientific research such as mirror neurons and the embodied Mind. The use of these models should encourage machine self-learning. Self-learning means autonomy, and autonomy needs strong AI development. It is becoming increasingly clear that autonomy is the condition of the sociality of the sobot. The article thus concludes that the relationship between cobot and sobot is the identification of a more general robot-automaton (rabota-automatos) relationship which, in the writer's opinion, is the essential basis and driving force behind the entire history of Robotics. [ABSTRACT FROM AUTHOR]

Collaborative workplaces are increasingly used in production systems. The possibility of direct collaboration between robots and humans brings many advantages, as it allows the simultaneous use of human and robotic strengths. However, collaboration between a collaborative robot and a human raises concerns about the safety of the interaction, the impact of the robot on human health, human efficiency, etc. Additionally, research is unexplored in the field of the collaborative robot's audio-visual effects on the worker's efficiency. Our study results contribute to the field of studying collaborative robots' audio-visual effects on the worker's behavior. In this research, we analyze the effect of the changing motion parameters of the collaborative robot (speed and acceleration) on the efficiency of the worker and, consequently, on the production process. Based on the experimental results, we were able to confirm the impact of robot speed and acceleration on the worker's efficiency in terms of assembly time. We also concluded that the sound level and presence of a visual barrier between the worker and robot by themselves have no effect on the worker's efficiency. The experimental part of the paper clearly identifies the impact of visualization on work efficiency. According to the results, the robot's audio-visual effects play a key role in achieving high efficiency and, consequently, justifying the implementation of a collaborative workplace. [ABSTRACT FROM AUTHOR]

The increasing usage of cobot applications reshapes work environments and working conditions, requiring specific advancements in organizational practices for health and safety. Enterprises should shift from a technocentric risk management approach to considering cobot application as socio-technical systems, for which a resilience engineering approach is beneficial. This study presents an instantiation of the resilience analysis grid in cobot applications with the aim of measuring resilience potentials in terms of the four cornerstones of resilience engineering (respond, learn, monitor, and anticipate). The assessment has been provided via a questionnaire to 15 companies making use of cobot applications. Results revealed that companies mainly focus on the risk assessment of cobot applications with a traditional view of machine-centric safety, paying less attention to assessing contexts and process variables. This observation seems to arise mainly due to the lack of formally available safety methods or limited guidance from technical standards. Additionally, traditional industrial approaches to risk management lack monitoring of several risks that are essential for managing resilience, defined as the adaptive capacity of people, organizations, and human-machine systems. In addition, companies strongly rely on data from the cobot manufacturer for their safety assessment. The resilience analysis grid was confirmed as a valuable assessment tool for the participating companies to identify improvement areas and assess health and safety from a resilience engineering perspective. [ABSTRACT FROM AUTHOR]

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Collaborative tasks in multiple systems have attracted considerable attention in contemporary manufacturing environments. Collaborative robots are representative agents for various collaborative industrial tasks. This study focuses on contactless delivery by considering multiple agents. A contactless delivery operation must be performed with well-synchronized cooperation among the sender, a receiver, and flying dynamics of the deliverable. The most challenging task is to predict the catching point of a thrown package by considering both collaborative robots. Accurate catching-point prediction and relevant operations were achieved using the proposed physics-informed neural network-based hybrid multi-stream deep learning framework. Various cooperative environments were considered using multi-modal input data and manufacturing conditions. The proposed framework incorporates these constraints, and the prediction is guided by flying dynamics and trajectory data. The effectiveness of the proposed framework was demonstrated by implementing multi-agent and related manufacturing environments in a digital twin system. The effectiveness of the proposed framework was proven experimentally using analyses and comparisons with existing machine learning methods. [ABSTRACT FROM AUTHOR]

Humanoid and collaborative robots find their application in numerous sectors, such as automotive, electrical and mechanical engineering, not excluding the field of bioengineering. They replace repetitive and often monotonous human activity. As the trend nowadays is for continuous optimization of production processes, their advantage is easy relocation and operative application to new tasks, which allows the automation of practically all manual work. A common feature of manipulators is the control of the positioning of the actuators, primarily by adjusting the parameters of the drive units. Feedback is often implemented through various sensors that provide real-time information. However, most of the sensors in use do not provide information that would allow obtaining data on the history of the operating load in order to assess the further safe and reliable operation of the mechanical parts. This paper presents a low-cost torque sensor that was proposed by modifying the design of an existing part. The torque sensor was developed on the principle of strain gauge measurement. The results of strain–stress analysis obtained by numerical modelling were experimentally validated under static and dynamic loading. Practical application is mainly the development and long-term testing of prototypes of various types of manipulators and collaborative robots, where high accuracy and repeatability of positioning are essential. [ABSTRACT FROM AUTHOR]

Objectives: Multiple generations of medical robots have revolutionized surgery. Their application to dental implants is still in its infancy. Co‐operating robots (cobots) have great potential to improve the accuracy of implant placement, overcoming the limitations of static and dynamic navigation. This study reports the accuracy of robot‐assisted dental implant placement in a preclinical model and further applies the robotic system in a clinical case series. Materials and Methods: In model analyses, the use of a lock‐on structure at robot arm‐handpiece was tested in resin arch models. In a clinical case series, patients with single missing teeth or edentulous arch were included. Robot‐assisted implant placement was performed. Surgery time was recorded. Implant platform deviation, apex deviation, and angular deviation were measured. Factors influencing implant accuracy were analyzed. Results: The in vitro results showed that with a lock‐on structure, the mean (SD) of platform deviation, apex deviation, and angular deviation were 0.37 (0.14) mm, 0.44 (0.17) mm, and 0.75 (0.29)°, respectively. Twenty‐one patients (28 implants) were included in the clinical case series, 2 with arches and 19 with single missing teeth. The median surgery time for single missing teeth was 23 (IQ range 20–25) min. The surgery time for the two edentulous arches was 47 and 70 min. The mean (SD) of platform deviation, apex deviation, and angular deviation was 0.54 (0.17) mm, 0.54 (0.11) mm, and 0.79 (0.22)° for single missing teeth and for 0.53 (0.17) mm, 0.58 (0.17) mm, and 0.77 (0.26)° for an edentulous arch. Implants placed in the mandible had significantly larger apex deviation than those in the maxilla. Conclusion: Cobot‐assisted dental implant placement showed excellent positional accuracy and safety in both the in vitro study and the clinical case series. More technological development and clinical research are needed to support the introduction of robotic surgery in oral implantology. Trial registered in ChiCTR2100050885. [ABSTRACT FROM AUTHOR]

Human-robot collaboration can be a powerful tool for increasing productivity in production systems by combining the strengths of humans and robots. Assembly operations, in particular, have shown great potential for utilizing the unique abilities of both parties. However, for robots to efficiently perform assembly tasks, components and parts must be presented in a known location and orientation, which is achieved through a process called parts feeding. Traditional automation methods for parts feeding, such as vibratory bowl feeders, are limited in their ability to accommodate variations in parts design, shape, location, and orientation, making them less flexible for use in human-robot collaboration. Recent advancements in machine vision technology have opened up new possibilities for flexible feeding systems in human-robot assembly cells. This paper explores the application of the vision system in the collaborative robot ABB Yumi and its ability in object detection. In this case, the characteristic of the vision system was determined experimentally by changing the light intensity on the test rig. The system was validated, if the angle of incidence of light affects the stability of the vision system. The results of the study demonstrate the efficiency of vision system in collaborative robot and provide insights into its industrial application. [ABSTRACT FROM AUTHOR]

Quality is crucial for modern organizations and sustainable quality management is key to this. Collaborative robots can help improve the quality of production flows. Currently, mass production flows may involve the use of equipment with nonconventional technologies implemented. The integration of collaborative robots and nonconventional technologies into production processes must be done in a qualitative and knowledge-based way. In this context, knowledge-based management plays an extremely important role in ensuring the success of organizations in the face of competition. It facilitates the learning, transfer, improvement and maintenance of knowledge within the organization, contributing to the provision of high-quality products and services. Collaborative robots have also represented a significant shift in the traditional paradigm of human-robot collaboration, transforming into an nonconventional technology that has helped break down the barrier between these two entities. The scientific paper explores the correlation between the four concepts: quality, collaborative robots, nonconventional technologies and knowledge-based management, to ensure the success of organizations. A parallel can also be found in the scientific work between the knowledge-based organization and the learning organization. [ABSTRACT FROM AUTHOR]

The global production tends towards more sustainable manufacturing, which forces manufacturers to constantly change and adapt. In our case, we are considering the FESTO CP LAB 400 production line, primarily designed for the training of personnel in the field of automation, which is essential for maintaining competitiveness in today's world. The production line consists of seven fully automated workstations and one manual assembly workstation, which represents the bottleneck of the production system. The paper presents a comparative study of the lines (human assembly vs. collaborative robot assembly) with an emphasis on economic and environmental aspects. The input parameters of the production line were obtained based on real-world measurements, while the assembly time of the collaborative robot was determined through simulation studies. The results of the study are presented graphically and numerically and confirm the contribution of the introduction of a collaborative robot to the assembly workstation in both financial and environmental terms. [ABSTRACT FROM AUTHOR]

The spread of cobotsin common industrial practice has led constructors to prefer the development of collaborative features that are necessary to prevent injuries to operators over the realization of simple kinematic structures for which the joints-to-workspace mapping is well known. An example is given by the replacement in serial robots of spherical wrists with safer solutions, where the danger of crushing and shearing is intrinsically avoided. Despite this tendency, the kinematic map between actuated joints and the Cartesian workspace remains of paramount importance for robot analysis and programming, deserving the attention of the research community. This paper proposes a closed-form solution for the inverse kinematics of a class of 6R robotic arms with six degrees of freedom and non-spherical wrists. The solutions are worked out by a single polynomial, of minimum degree, in terms of one of the positioning parameters chosen for the description of the robot posture. The roots of such a polynomial are then back-substituted to determine all the remaining unknowns. A numerical example is finally shown to verify the validity of the proposed implementation for a commercial collaborative robot. [ABSTRACT FROM AUTHOR]

While traditional industrial robots participate in repetitive manufacturing processes from behind caged safety enclosures, collaborative robots (cobots) offer a highly flexible and human-interactive solution to manufacturing automation. Rather than operating from within cages, safety features such as force and proximity sensors and programmed protection zones allow cobots to work safely, close to human workers. Cobots can be configured to either stop or slow their motion if they come in contact with a human or obstacle or enter a protection zone, which may be a high pedestrian traffic area. In this way, a task can be divided into sub-processes allocated to the cobot or the human based on suitability, capability or human preference. The flexible nature of the cobot makes it ideal for low-volume, 'just-in-time' manufacturing; however, this requires frequent reprogramming of the cobot to adapt to the dynamic processes. This paper reviews relevant cobot programming and control methods currently used in the manufacturing industry and alternative solutions proposed in the literature published from 2018 to 2023. The paper aims to (1) study the features and characteristics of existing cobot programming and control methods and those proposed in the literature, (2) compare the complexity of the task that the cobot is to perform with the skills needed to program it, (3) determine who is the ideal person to perform the programming role, and (4) assess whether the cobot programming and control methods are suited to that person's skillset or if another solution is needed. The study is presented as a guide for potential adopters of cobots for manufacturing and a reference for further research. [ABSTRACT FROM AUTHOR]

A patina is essentially the weathered look a piece of leather takes on as it ages. The patina finishing aspect can be also generated or grown artificially by scrubbing the leather surface with specific products. These kinds of manual finishing operations on small objects are delicate and regularly need slight corrections carried out by skilled artisans, which adds complexity to the process automation and implies various key aspects to consider. This research presents a novel approach for automatic and semiautomatic shoe patina growing in the footwear industry using a new co-creative method based on cooperative robotics. The system automates the process in pursuit of operator time-saving without reducing the work finishing quality. For this purpose, the use of a collaborative robot with a built-in constant contact force control and a collaborative tool are used in this research. The use of both tools in complementarity with the knowledge of the craftsman leads the robot end-effector adaptation to the inherent curved surfaces over the shoe. Besides, some orientation corrections are applied based on the CAD model for the task to be accurately accomplished. The solution has been successfully integrated in a real production line, and it is currently in use. [ABSTRACT FROM AUTHOR]

This paper proposes a zero-moment control torque compensation technique. After compensating the gravity and friction of the robot, it must overcome a small inertial force to move in compliance with the external force. The principle of torque balance was used to realise the zero-moment dragging and teaching function of the lightweight collaborative robot. The robot parameter identification based on the least square method was used to accurately identify the robot torque sensitivity and friction parameters. When the robot joint rotates at a low speed, it can approximately satisfy the torque balance equation. The experiment uses the joint position and the current motor value collected during the whole moving process under the low-speed dynamic balance as the excitation signal to realise the parameter identification. After the robot was compensated for gravity and static friction, more precise torque control was realised. The zero-moment dragging and teaching function of the robot was more flexible, and the drag process was smoother. [ABSTRACT FROM AUTHOR]

As intelligent operating assistants, collaborative robots have opened up a wide range of application scenarios in fields of industry, service and medical treatment. In order to explore the dynamic characteristics of collaborative robots and improve the accuracy of terminal positioning, this paper takes the KUKA LBR lightweight humanoid arm collaborative robot model as an example for research. Based on the RBF neural network and the synovial control algorithm, the dynamic control strategy of the collaborative robot is designed and the dynamic characteristics and end position error are analyzed. Parameter identification and error compensation of collaborative robots are carried out based on the Levenberg-Marquardt nonlinear damping least squares algorithm. The ADAMS-Matlab joint simulation shows that the dynamic control effect of a sliding mode controller based on the RBF neural network is better. The average terminal error under an extreme working condition is about 4.7 mm, which is mainly due to the influence of gravity load. After variable parameter error compensation, the average terminal error is less than 0.2 mm, which effectively improves the position accuracy and provides a theoretical basis for the research of collaborative robot control and error compensation. [ABSTRACT FROM AUTHOR]

Parameter identification of the dynamic model of collaborative robots is the basis of the development of collaborative robot motion state control, path tracking, state monitoring, fault diagnosis, and fault tolerance systems, and is one of the core contents of collaborative robot research. Aiming at the identification of dynamic parameters of the collaborative robot, this paper proposes an identification algorithm based on weighted least squares and random weighted particle swarm optimization (WLS-RWPSO). Firstly, the dynamics mathematical model of the robot is established using the Lagrangian method, the dynamic parameters of the robot to be identified are determined, and the linear form of the dynamics model of the robot is derived taking into account the joint friction characteristics. Secondly, the weighted least squares method is used to obtain the initial solution of the parameters to be identified. Based on the traditional particle swarm optimization algorithm, a random weight particle swarm optimization algorithm is proposed for the local optimal problem to identify the dynamic parameters of the robot. Thirdly, the fifth-order Fourier series is designed as the excitation trajectory, and the original data collected by the sensor are denoised and smoothed by the Kalman filter algorithm. Finally, the experimental verification on a six-degree-of-freedom collaborative robot proves that the predicted torque obtained by the identification algorithm in this paper has a high degree of matching with the measured torque, and the established model can reflect the dynamic characteristics of the robot, effectively improving the identification accuracy. [ABSTRACT FROM AUTHOR]

This paper presents a comparison between two different 6R articulated robot architectures, one with a spherical wrist and the other with a non-spherical wrist and three consecutive parallel axes, which are found mainly in collaborative arms. The performance of the two architectures has been evaluated in terms of linear and rotational velocity using the Kinematic Directional Index (KDI). The results highlight the relation between the robot's velocity along a direction and the joint velocities. In this way, the proposed approach allows the evaluation of the best performance in a direction and the joints that limit the considered motion. [ABSTRACT FROM AUTHOR]

The paper presents the use of simulation modelling methods to evaluate the impact of the collaborative workplaces (human-robot collaboration) importance in correlation to the sustainable manufacturing. Based on an example, numerical simulation results of an existing manual assembly workplace and a newly proposed collaborative workplace are presented using production parameters that describe all three key aspects of sustainable manufacturing: economic, social and environmental aspect. A datadriven simulation model was used, mainly using the input parameters of the real-world production system and numerical assumptions obtained from the literature, with the main objective of detailing the impact on the sustainable orientation of the production process. The results presented in the paper demonstrate the high suitability of simulation modelling methods in the evaluation of existing and newly proposed technologies from the sustainable manufacturing point of view. The results demonstrate that collaborative workplaces, if implemented appropriately and using correct input data, are a possible solution that can cope with limited human resources and ensure high production efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we propose the estimation of contact force in a collaborative robot without explicit force-sensing based on the adaptive third-order sliding mode observer. An adaptive third-order sliding mode observer was designed to estimate the contact force based only on the position measurement. The information from the observer was used for admittance control and emergent stop control when the robot interacts with a human. The experimental results with the emergent stop control and admittance control, using the proposed contact force estimation for the 3-DOF AT2-FARA robot manipulator, illustrate the capability of the proposed system in real-world application. [ABSTRACT FROM AUTHOR]

This work presents one example from a set of technologies that aim at improving the efficiency of manufacturing processes of aircraft components in one of Airbus Defence and Space plants in regards to environmental aspects. Among the proposed technologies, one relates to the automation of two key manufacturing steps of the reference technology in the composite manufacturing of omega stringers: 1) lamination of main omega stringer structure through an Automated Fiber Placement robotic process; and 2) cobotic pick‐and‐place process for Carbon Fiber Reinforced Polymer patches. To evaluate potential environmental benefits, Fraunhofer performs a gate‐to‐gate study using as main parameter the "Work effort unit," in this case representing the average energy consumption per productive hour in a typical assembly factory. When comparing the results for the composite part manufacturing by hand lay‐up with the use of collaborative robots, the key technical parameter is the reduction in lead time. While production using robots consume additional electricity when compared to human workers, automation significantly shortens lead times (‐74%), resulting in lower energy consumption per manufactured unit. The results indicate that this new technology from Airbus Defence and Space can potentially improve the overall environmental performance of composite parts during their manufacture. [ABSTRACT FROM AUTHOR]

Summary: Today, demandsin industrial manufacturing mandate humans to work with large-scale industrial robots, and this collaboration may result in dangerous conditions for humans. To deal with this situation, this work proposes a novel approach for redundant large-scale industrial robots. In the proposed approach, an admittance controller is designed to regulate the interaction between the end effector of the robot and the human. Additionally, an obstacle avoidance algorithm is implemented in the null space of the robot to prevent any possible unexpected collision between the human and the links of the robot. After safety performance of this approach is verified via simulations and experimental studies, the effect of the parameters of the admittance controller on the performance of collaboration in terms of both accuracy and total human effort is investigated. This investigation is carried out via 8 experiments by the participation of 10 test subjects in which the effect of different admittance controller parameters such as mass and damper are compared. As a result of this investigation, tuning insights for such parameters are revealed. [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 scientific paper proposes a pragmatic perspective of presenting the most important theoretical and practical issues on the process of manufacturing by electrical erosion and integration of collaborative robots in an industrial organization, processes linked to the possibility of using new technologies in industry. Collaborative robots are an important viable alternative to new ways of streamlining process management in modern industrial organizations and in this article is presented the possibility of their integration in a processing flow based on electrical erosion. The research presents in an elegant way the possibilities of streamlining everything that means the process of manufacturing by electrical erosion using collaborative robots. The point of view presented is only a small part of what involves the implementation of such opportunities with a deep novelty. Through this scientific paper the authors are offering new opportunities to implement the concepts of efficiency and effectiveness in the process of manufacturing by electrical erosion in industry. [ABSTRACT FROM AUTHOR]

Featured Application: The article gives a detailed description on how to implement a custom force control for collaborative robots without knowing all the internal parameters. The methodology presented can be used in any manufacturing process capable of being carried out by a collaborative robot. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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". [ABSTRACT FROM AUTHOR]

Collaborative robots are increasingly being used in dynamic and semi-structured environments because of their ability to perform physical Human–Robot Interaction (pHRI) to ensure safety. Therefore, it is crucial to model the dynamics of collaborative robots during pHRI to gain valuable insights into the system's behavior when in contact with humans. In this work, a generic dynamic model is proposed for the quasi-static contact phase of pHRI, which considers the interaction dynamics and the complete structural dynamics of the collaborative robot. Moreover, a hybrid physics-informed neural network (PINN) is proposed, which utilizes a recurrent neural network (RNN) and the Runge–Kutta method to identify the joint dynamic parameters without complicated regressor construction. Experiments are conducted using a UR3e collaborative robot, and the PINN is trained using the acquired data. The results demonstrate the effectiveness of the PINN in identifying joint dynamics without prior knowledge, and the dynamic simulation of pHRI is consistent with the experimental results. The proposed model and PINN-based identification approach have the potential to improve safety and productivity in industrial environments by facilitating the control of pHRI. • A comprehensive model for cobot dynamics with joint flexibility and pHRI. • A PINN-based parameter identification algorithm for estimating joint dynamics. • Experimental validations of the PINN and the robot dynamic model with pHRI. [ABSTRACT FROM AUTHOR]

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