Collaborative Robotics Applications Research Articles

Research Status and Development Trend of Multi-arm Collaborative Robots

Abstract: Industrial robots are mainly used in metal forming, automotive, and electrical and electronics industries. After decades of unremitting efforts, industrial robots have achieved great success. However, problems such as low safety, weak environmental adaptability, and insufficient humancomputer interaction ability of industrial robots have greatly limited the application of industrial robots, and multi-arm collaborative robots came into being in this case. Multi-arm collaborative robots offer high flexibility and precision. Over the years, the application and development of multiarm collaborative robots have been paid more and more attention. This paper aims to summarize the patents related to multi-arm cooperative robots, including their principles, classification, latest progress and future development, in order to meet the needs of the real world. According to the structural characteristics of multi-arm collaborative robots and the requirements of multi-arm collaborative robots application field, the most typical mobile collaborative robots and stationary dual-arm collaborative robots in multi-arm collaborative robots are summarized. By investigating various patents of multi-arm collaborative robots the main problems of multi-arm collaborative robots are summarized and analyzed, such as collisions or conflicts between robotic arms, low power-to-weight ratio, loose structures, and heavy weight of the robot body. In addition, the development trend of multi-arm collaborative robots is also discussed. Multi-arm robots have broad prospects and potential in future applications and development. With the advancement of new technologies, multi-arm collaborative robots will become more efficient, intelligent, safe, and flexible. More relevant patents are expected to be invented in the future.

Multi-scale progressive fusion-based depth image completion and enhancement for industrial collaborative robot applications

Multi-scale progressive fusion-based depth image completion and enhancement for industrial collaborative robot applications

On the Evaluation of Diverse Vision Systems towards Detecting Human Pose in Collaborative Robot Applications.

Tracking human operators working in the vicinity of collaborative robots can improve the design of safety architecture, ergonomics, and the execution of assembly tasks in a human-robot collaboration scenario. Three commercial spatial computation kits were used along with their Software Development Kits that provide various real-time functionalities to track human poses. The paper explored the possibility of combining the capabilities of different hardware systems and software frameworks that may lead to better performance and accuracy in detecting the human pose in collaborative robotic applications. This study assessed their performance in two different human poses at six depth levels, comparing the raw data and noise-reducing filtered data. In addition, a laser measurement device was employed as a ground truth indicator, together with the average Root Mean Square Error as an error metric. The obtained results were analysed and compared in terms of positional accuracy and repeatability, indicating the dependence of the sensors' performance on the tracking distance. A Kalman-based filter was applied to fuse the human skeleton data and then to reconstruct the operator's poses considering their performance in different distance zones. The results indicated that at a distance less than 3 m, Microsoft Azure Kinect demonstrated better tracking performance, followed by Intel RealSense D455 and Stereolabs ZED2, while at ranges higher than 3 m, ZED2 had superior tracking performance.

Application of Collaborative Robots for Increasing Productivity in an Eyeglasses Lenses Manufacturer

Application of Collaborative Robots for Increasing Productivity in an Eyeglasses Lenses Manufacturer

Systems-theoretic interdependence analysis in robot-assisted warehouse management

The safe and efficient application of collaborative robots requires an understanding of actual work practices transformation, emerging from the adoption of new technological instruments. Functional systems-thinking is largely absent in literature about collaborative robot applications. In this context, this study proposes a framework that combines two safety analysis methods, being the Functional Resonance Analysis Method and Interdependence Analysis. Both safety and efficiency are examined by selected case study highlights to gain an in-depth understanding of human operators’ role as the central driver of human–machine (eco)systems in a warehouse distribution system, in which warehouse robot assistance is provided. Whereas the Functional Resonance Analysis Method first maps the work system interactions as a whole, Interdependence Analysis is subsequently applied to investigate individual inter-agent exchanges by the principles of Observability, Predictability, and Directability as a core principle for goal coordination between multiple agents, including warehouse robot agents. The case study examples reveal the combined effects of the working system environment and the robot application but also demonstrate possible operational solutions to deal with socio-technical complexity.

An Online Toolkit for Applications Featuring Collaborative Robots Across Different Domains

Collaborative robots (cobots) are being applied in areas such as healthcare, rehabilitation, agriculture and logistics, beyond the typical manufacturing setting. This is leading to a marked increase in the number of cobot stakeholders with little or no experience in traditional safety engineering. Considering the importance of human safety in collaborative robotic applications, this is currently proving to be a barrier to more widespread cobot usage. A web-based Toolkit that targets cobot end-users and manufacturers with varying levels of safety expertise was developed, helping them to understand how to consider the safety of their cobot applications. In this work, we will provide an overview of the state of the art for ensuring cobot safety, highlight the support provided by the “COVR Toolkit” and introduce three examples where third parties applied the Toolkit for their collaborative robotics application.

Visual quality and safety monitoring system for human-robot cooperation

Efficient workspace awareness is critical for improved interaction in cooperative and collaborative robotic applications. In addition to safety and control aspects, quality-related tasks such as the monitoring of manual activities and the final quality assessment of the results are also required. In this context, a visual quality and safety monitoring system is developed and evaluated. The system integrates close-up observation of manual activities and posture monitoring. A compact single-camera stereo vision system and a time-of-flight depth camera are used to minimize the interference of the sensors with the operator and the workplace. Data processing is based on a deep learning to detect classes related to quality and safety aspects. The operation of the system is evaluated while monitoring a human-robot manual assembly task. The results show that the system ensures a high level of safety, provides reliable visual feedback to the operator on errors in the assembly process, and inspects the finished assembly with a low critical error rate.

Role of Reference Frames for a Safe Human–Robot Interaction

Safety plays a key role in human–robot interactions in collaborative robot (cobot) applications. This paper provides a general procedure to guarantee safe workstations allowing human operations, robot contributions, the dynamical environment, and time-variant objects in a set of collaborative robotic tasks. The proposed methodology focuses on the contribution and the mapping of reference frames. Multiple reference frame representation agents are defined at the same time by considering egocentric, allocentric, and route-centric perspectives. The agents are processed to provide a minimal and effective assessment of the ongoing human–robot interactions. The proposed formulation is based on the generalization and proper synthesis of multiple cooperating reference frame agents at the same time. Accordingly, it is possible to achieve a real-time assessment of the safety-related implications through the implementation and fast calculation of proper safety-related quantitative indices. This allows us to define and promptly regulate the controlling parameters of the involved cobot without velocity limitations that are recognized as the main disadvantage. A set of experiments has been realized and investigated to demonstrate the feasibility and effectiveness of the research by using a seven-DOF anthropomorphic arm in combination with a psychometric test. The acquired results agree with the current literature in terms of the kinematic, position, and velocity aspects; use measurement methods based on tests provided to the operator; and introduce novel features of work cell arranging, including the use of virtual instrumentation. Finally, the associated analytical–topological treatments have enabled the development of a safe and comfortable measure to the human–robot relation with satisfactory experimental results compared to previous research. Nevertheless, the robot posture, human perception, and learning technologies would have to apply research from multidisciplinary fields such as psychology, gesture, communication, and social sciences in order to be prepared for positioning in real-world applications that offer new challenges for cobot applications.

COBOT Applications—Recent Advances and Challenges

This study provides a structured literature review of the recent COllaborative roBOT (COBOT) applications in industrial and service contexts. Several papers and research studies were selected and analyzed, observing the collaborative robot interactions, the control technologies and the market impact. This review focuses on stationary COBOTs that may guarantee flexible applications, resource efficiency, and worker safety from a fixed location. COBOTs offer new opportunities to develop and integrate control techniques, environmental recognition of time-variant object location, and user-friendly programming to interact safely with humans. Artificial Intelligence (AI) and machine learning systems enable and boost the COBOT’s ability to perceive its surroundings. A deep analysis of different applications of COBOTs and their properties, from industrial assembly, material handling, service personal assistance, security and inspection, Medicare, and supernumerary tasks, was carried out. Among the observations, the analysis outlined the importance and the dependencies of the control interfaces, the intention recognition, the programming techniques, and virtual reality solutions. A market analysis of 195 models was developed, focusing on the physical characteristics and key features to demonstrate the relevance and growing interest in this field, highlighting the potential of COBOT adoption based on (i) degrees of freedom, (ii) reach and payload, (iii) accuracy, and (iv) energy consumption vs. tool center point velocity. Finally, a discussion on the advantages and limits is summarized, considering anthropomorphic robot applications for further investigations.

Picking with a robot colleague: A systematic literature review and evaluation of technology acceptance in human–robot collaborative warehouses

Just-in-time delivery, shorter product life cycles, demographic changes, and the Covid-19 pandemic have driven the industrial application of collaborative robots in warehouses. These robots work alongside humans, increasing their productivity and relieving them of repetitive or strenuous tasks. However, human workers can be reluctant to collaborate with robots owing to certain fears; for example, they may be concerned about job loss, stress, expected effort, or risk to physical integrity. These concerns can negatively impact the acceptance of human–robot collaboration (HRC). As the literature on this topic is fragmented, this study analyzes HRC acceptance in warehouses based on the Unified Theory of Acceptance and Use of Technology. We identify, classify, and analyze studies examining HRC acceptance in warehouses using a systematic literature review methodology. A framework is established to guide the analysis of performance expectancy, effort expectancy, (perceived) occupational safety, psychosocial, and legal and privacy factors. The results indicate the importance of corporate infrastructure and consideration of cognitive factors in particular. The findings of this study will support future research on HRC in warehouses and provide guidance for managers regarding HRC applicability.

Guidelines for the integration of cognitive ergonomics in the design of human-centered and collaborative robotics applications

In the context of Industry 4.0, cognitive ergonomics is crucial for improving the working conditions and the psychosocial well-being of operators interacting with even more advanced and smart machines, as well as for the enhancement of production performances. Nevertheless, this topic is often neglected or ignored when implementing human-robot interaction in industrial settings. Starting from the results obtained from previous studies, this work proposes a structured process to develop and preliminarily validate a set of guidelines to support non-experts in human factors at the early stages of the design of human-centered and collaborative applications. A systematic analysis of the scientific literature has been performed by an interdisciplinary team of researchers to identify relevant results on the topic. Successively, the guidelines have been developed starting from such an analysis by considering the target group and the final aim of the work. This phase involved the analysis, classification, summary, and abstraction of relevant statements and results from the selected articles, as well as the update of the previous set of guidelines. The guidelines have been preliminarily validated by an external team of researchers currently doing research in the field. Qualitative feedback on understandability and relevance has been collected to improve the guidelines before further investigations.

Assessing the Influence of Collaborative Technology Adoption—Mediating Role of Sociotechnical, Organizational, and Economic Factors

The study investigated the factors that influence the adoption of collaborative robots in the manufacturing sector in Russia from sociotechnical, organizational, and economic point of views. The study was driven by the increasing technological innovation in the manufacturing sector, especially in the use of robots and collaborative robot applications in daily manufacturing, flexibility, and operations activities. The study was a quantitative, descriptive survey that relied on primary data from respondents with varied experiences in the manufacturing sector in Russia. The study employed a total of 351 respondents selected for their insights into the application of robotics in the manufacturing process in Russia. The model adopted for the study was tested using confirmatory factor analysis (CFA), reliability, and validity analysis. The hypotheses of the study were evaluated using partial least-squares analysis. The results revealed that the adoption of collaborative robots was influenced by organizational factors and economic factors. Perceived performance improvement was significantly influenced by collaborative robot adoption and sociotechnical systems. The study recommended that the stakeholders in Russia’s manufacturing sector should improve their training, management support, perceived innovativeness, and prior experience to enhance the adoption of collaborative robots and flexibility in design.

Use of Interaction Design Methodologies for Human–Robot Collaboration in Industrial Scenarios

The key concept of collaborative robotics is represented by the presence of a strict interaction between a human user and the robotic system. As such, the study of the interaction is of paramount importance for a successful implementation of the system. In this article, we propose a novel approach to address the problem of designing a collaborative robotic system for industrial applications, focusing on the characteristics of the interaction. In particular, we will propose a set of methodologies focused on interaction design, inspired by those used for the design of user interfaces. These methodologies will allow the design of collaborative robotic systems following a user-centered approach, thus putting emphasis not only on safety and adaptability of the robotic systems (which have been widely addressed in the literature), but also on the interaction experience. While the proposed methodology was developed considering general collaborative robotics applications, two real industrial case studies were considered, to instantiate the considered framework and showcase its applicability to the real-world domain. Note to Practitioners—This article aims at bridging the gap between interaction design and collaborative robotics. In particular, the proposed methodology will represent a toolset for robotic experts (researchers and system integrators), for understanding the user experience and designing the robotic system ensuring an effective interaction. In fact, while robotics experts are typically well aware of issues and methodologies related to technological and application aspects, they often tend to ignore the principles of interaction. Such principles are commonly adopted in the design of computer-based human–machine interfaces or web applications, but, to the best of the authors’ knowledge, have never been applied to the design of collaborative robotic systems for industrial applications. Hence, this article will serve as a fundamental step to bring interaction design principles into the robot integration domain.

Transparency Analysis of a Passive Heavy Load Comanipulation Arm

For collaborative robotics applications, many systems have addressed general handling issues in recent years. Depending on the industrial context, these systems bring physical and cognitive feelings that result in the acceptance of their users. Transparency qualifies the ability of a robot to follow the movements imposed by the operator without noting any resistant effort. The objective of this article is to develop a methodology that mixes the approach highlighting the human factors and their correlation to robotic criteria in the case of a passive manipulation arm with six degrees of freedom produced by the Neoditech company. An exploratory study was then conducted to measure criteria such as time, speed, and effort during manipulation along with criteria based on a technological level, personality and technology acceptance model-method questionnaires. From there, we uncovered a correlation between the user’s personality, particularly their lack of neuroticism, and their means of evaluating the device through its usefulness, comfort, and indicators of mechanical behavior. This study is a preliminary analysis of user behaviors and traits that affect technological acceptance when dealing with a comanipulation arm. This work offers a framework for similar future analyses and recommends mechanical adjustments to the arm for increased user acceptance.

Interdependence Analysis in collaborative robot applications from a joint cognitive functional perspective

This paper sets up a framework to assess co-agency in human-robot interactions, and applies it specifically to the socio-technical safety analysis of collaborative robots. We also examine to what extent the concept of Situation Awareness can be applied to assess collaborative robots as efficient team members in socio-technical systems. We explain some theoretical concerns with traditional concepts of Situation Awareness and defend why the concept of Joint Cognitive Systems, which maps the conceptualization of the cognitive system onto the work system as a whole, is best suited for issues of distributed cognition and controllability in human-robot interaction. Thereafter we present a five-step methodology specifically conceived for cobot applications serving the aim of goal coordination between multiple agents by functional interactions. The proposed framework merges two existing safety and resilience analysis methods, being the Functional Resonance Analysis Method and Interdependence Analysis. These methods are used in combination to assess shared control in safe and efficient human-robot interaction from a systems-thinking perspective. This allows to describe the systemic conditions for Distributed Situation Awareness in terms of observable system interactions and as an emergent object of distributed cognition. Instead of looking at undesirable safety outcomes, we have imposed the focus of co-agency as the unit of analysis in line with the Joint Cognitive Systems perspective. The theoretical insights from this paper are additionally applied to a hypothetical but credible demonstration case study with collaborative warehouse robots.

Novel Approach Using Risk Analysis Component to Continuously Update Collaborative Robotics Applications in the Smart, Connected Factory Model

Building on the idea of Industry 4.0, new models of the highly connected factory that leverage factory-generated data to introduce cost-effective automation and involve the human worker for creating higher added value are possible. Within this context, collaborative robots are becoming more common in industry. However, promises regarding flexibility cannot be satisfied due to the challenging process of ensuring human safety. This is because current regulations and standards require updates to the risk assessment for every change to the robotic application, including the parts involved, the robotic components, and the type of interaction within the workspace. This work presents a novel risk analysis software tool that was developed to support change management for adaptive collaborative robotic systems in the connected factory model. The main innovation of this work is the tool’s ability to automatically identify where changes have been made to components or processes within a specific application through its integration with a connected factory architecture. This allows a safety expert to easily see where updates to the risk assessment are required, helping them to maintain conformity with the CE marking process despite frequent changes. To evaluate the benefits of this tool, a user study was performed with an exemplary use-case from the SHOP4CF project. The results show that this newly developed technology for risk assessment has better usability and lower omission errors when compared to existing methods. Therefore, this study underlines the need for tools that can help safety engineers cope with changes in flexible robotics applications and reduce omission errors.

Vibration suppression of collaborative robot based on modified trajectory planning

PurposeThe paper aims to reduce the low-frequency resonance and residual vibration of the robot during the operation, improve the working accuracy and efficiency. A reduced weight and large load-to-weight ratio can improve the practical application of a collaborative robot. However, flexibility caused by the reduced weight and large load-to-weight ratio leads to low-frequency resonance and residual vibration during the operation of the robot, which reduces the working accuracy and efficiency. The vibrations of the collaborative robot are suppressed using a modified trajectory-planning method.Design/methodology/approachA rigid-flexible coupling dynamics model of the collaborative robot is established using the finite element and Lagrange methods, and the vibration equation of the robot is derived. Trajectory planning is performed with the excitation force as the optimization objective, and the trajectory planning method is modified to reduce the vibration of the collaborative robot and ensure the precision of the robot terminal.FindingsThe vibration amplitude is reduced by 80%. The maximum torque amplitude of the joint before the vibration suppression reaches 50 N·m. After vibration suppression, the maximum torque amplitude of the joint is 10 N·m, and the resonance phenomenon is eliminated during the operation process. Consequently, the effectiveness of the modified trajectory planning method is verified, where the vibration and residual vibration in the movement of the collaborative robot are significantly reduced, and the positioning accuracy and working efficiency of the robot are improved.Originality/valueThis method can greatly reduce the vibration and residual vibration of the collaborative robot, improve the positioning accuracy and work efficiency and promote the rapid application and development of collaborative robots in the industrial and service fields.

Application, Development and Future Opportunities of Collaborative Robots (Cobots) in Manufacturing: A Literature Review

The rapid development of robot technology has introduced a substantial impact on manufacturing. Numerous studies have been carried out to apply collaborative robots (cobots) to address manufacturing productivity and ergonomics issues, which has brought extensive opportunities. In this context, a systematic literature search in the Web of Science, Scopus, and Google Scholar databases was carried out by electronic and manual search. Thus, 59 relevant contributions out of 4488 studies were analyzed by using preferred reporting items for systematic reviews and meta-analysis (PRISMA). To provide an overview of the different results, studies are summarized according to the following criteria: country, author, year, study design, robot category, results, and future opportunities. The effects of cobots on safety, system design, workplace design, task scheduling, productivity, and ergonomics are discussed to provide a better understanding of the application of cobots in manufacturing. To incentive future research, this paper reviews the development of cobots in manufacturing and discusses future opportunities and directions from cobots and manufacturing system perspectives. This paper provides novel and valuable insights into cobots application and illustrates potential developments of future human-cobot interaction.

A method to enhance the flexibility of collaborative human-robot workspaces through an extended safety perspective

For the adaptation of a process in a flexible production environment, robotic systems are basically a suitable option to ensure the required agility. In case of a human-robot work system, however, the flexibility of a robot is currently severely limited due to safety reasons; therefore, new tasks for the robot can only be implemented with significant additional effort. In this paper we present a method for the flexibilization of collaborative robot applications within the constraints of robot safety as defined by ISO/TS 15066. We will show how an in-depth analysis of foreseeable tasks during the start-up phase of a collaborative human-robot work system provides the basis for both, a flexible as well as safe use. An expert system and suitable mathematical models ensure these modifications of tasks and changes in the workplace can be automatically evaluated in terms of safety. As a result, even non-safety-experts can make modifications and operate the system without imposing additional risks.

Innovative Collaborative Method for Interaction between a Human Operator and Robotic Manipulator Using Pointing Gestures

The concept of “Industry 4.0” relies heavily on the utilization of collaborative robotic applications. As a result, the need for an effective, natural, and ergonomic interface arises, as more workers will be required to work with robots. Designing and implementing natural forms of human–robot interaction (HRI) is key to ensuring efficient and productive collaboration between humans and robots. This paper presents a gestural framework for controlling a collaborative robotic manipulator using pointing gestures. The core principle lies in the ability of the user to send the robot’s end effector to the location towards, which he points to by his hand. The main idea is derived from the concept of so-called “linear HRI”. The framework utilizes a collaborative robotic arm UR5e and the state-of-the-art human body tracking sensor Leap Motion. The user is not required to wear any equipment. The paper describes the overview of the framework’s core method and provides the necessary mathematical background. An experimental evaluation of the method is provided, and the main influencing factors are identified. A unique robotic collaborative workspace called Complex Collaborative HRI Workplace (COCOHRIP) was designed around the gestural framework to evaluate the method and provide the basis for the future development of HRI applications.