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The purpose of this paper is to provide a novel methodology based on two-level protection for ensuring safety of the moving human who enters the robot’s workspace, which is significant for dealing with the problem of human security in a human-robot coexisting environment.

In this system, anyone who enters the robot’s working space is detected by using the Kinect and their skeletons are calculated by the interval Kalman filter in real time. The first-level protection is mainly based on the prediction of the human motion, which used Gaussian mixture model and Gaussian Mixture Regression. However, even in cases where the prediction of human motion is incorrect, the system can still safeguard the human by enlarging the initial bounding volume of the human as the second-level early warning areas. Finally, an artificial potential field with some additional avoidance strategies is used to plan a path for a robot manipulator.

Experimental studies on the GOOGOL GRB3016 robot show that the robot manipulator can accomplish the predetermined tasks by circumventing the human, and the human does not feel dangerous.

This study presented a new framework for ensuring human security in a human-robot coexisting environment, and thus can improve the reliability of human-robot cooperation.

As service robots increasingly interact with customers at the service encounter, they will inevitably become an integral part of employee's work environment. This research investigates frontline employee's perceptions of collaborative service robots (CSR) and introduces a new framework, willingness to collaborate (WTC), to better understand employee–robot interactions in the workplace.

Drawing on appraisal theory, this study employed an exploratory research approach to investigate frontline employees' cognitive appraisal of service robots and their WTC with their nonhuman counterparts in service contexts. Data collection consisted of 36 qualitative problem-centered interviews. Following an iterative thematic analysis, the authors introduce a research framework of frontline employees' WTC with service robots.

First, this study demonstrates that the interaction between frontline employees and service robots is a multistage appraisal process based on adoption-related perceptions. Second, it identifies important attributes across three categories (employee, robot and job attributes) that provide a foundation to understand the appraisal of CSRs. Third, it presents four employee personas (supporter, embracer, resister and saboteur) that provide a differentiated perspective of how service employee–robot collaboration may differ.

The article identifies important factors that enable and restrict frontline service employees' (FSEs’) WTC with robots.

This is the first paper that investigates the appraisal of CSRs from the perspective of frontline employees. The research contributes to the limited research on human–robot collaboration and expands existing technology acceptance models that fall short to explain post-adoptive coping behavior of service employees in response to service robots in the workplace.

Recent years have seen a technological change, Industry 4.0, in the manufacturing industry. Human–robot cooperation, a new application, is increasing and facilitating collaboration without fences, cages or any kind of separation. The purpose of the paper is to review mainstream academic publications to evaluate the current status of human–robot cooperation and identify potential areas of further research.

A systematic literature review is offered that searches, appraises, synthetizes and analyses relevant works.

The authors report the prevailing status of human–robot collaboration, human factors, complexity/ programming, safety, collision avoidance, instructing the robot system and other aspects of human–robot collaboration.

This paper identifies new directions and potential research in practice of human–robot collaboration, such as measuring the degree of collaboration, integrating human–robot cooperation into teamwork theories, effective functional relocation of the robot and product design for human robot collaboration.

This paper will be useful for three cohorts of readers, namely, the manufacturers who require a baseline for development and deployment of robots; users of robots-seeking manufacturing advantage and researchers looking for new directions for further exploration of human–machine collaboration.

This study aims to realize natural and effort-saving motion behavior and improve effectiveness for different operators in human–robot force cooperation.

The parameter of admittance model is identified by deep deterministic policy gradient (DDPG) to realize human–robot force cooperation for different operators in this paper. The movement coupling problem of hybrid robot is solved by realizing position and pose drags. In DDPG, minimum jerk trajectory is selected as the reward objective function, and the variable prioritized experience replay is applied to balance the exploration and exploitation.

A series of simulations are implemented to validate the superiority and stability of DDPG. Furthermore, three sets of experiments involving mass parameter, damping parameter and DDPG are implemented, the effect of DDPG in real environment is validated and could meet the cooperation demand for different operators.

DDPG is applied in admittance model identification to realize human–robot force cooperation for different operators. And minimum jerk trajectory is introduced into reward objective to meet requirement of human arm free movements. The algorithm proposed in this paper could be further extended in the other operation task.

The purpose of this paper is to eliminate instability which may occur when a human stiffens his arms in physical human–robot interaction by estimating the human hand stiffness and presenting a modified vibration index.

Human hand stiffness is first estimated in real time as a prior indicator of instability by capturing the arm configuration and modeling the level of muscle co-contraction in the human’s arms. A time-domain vibration index based on the interaction force is then modified to reduce the delay in instability detection. The instability is confirmed when the vibration index exceeds a given threshold. The virtual damping coefficient in admittance controller is adjusted accordingly to ensure stability in physical human–robot interaction.

By estimating the human hand stiffness and modifying the vibration index, the instability which may occur in stiff environment in physical human–robot interaction is detected and eliminated, and the time delay is reduced. The experimental results demonstrate significant improvement in stabilizing the system when the human operator stiffens his arms.

The originality is in estimating the human hand stiffness online as a prior indicator of instability by capturing the arm configuration and modeling the level of muscle co-contraction in the human’s arms. A modification of the vibration index is also an originality to reduce the time delay of instability detection.

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.

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.

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.

A new automated testing process in combination with a processing algorithm was developed.

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.

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.

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.

To promote the intuitiveness of collaborative tasks, the negotiation ability of humans with each other has inspired a large amount of studies aimed at reproducing the capacity in physical human-robot interaction (pHRI). This paper aims to promote mutual adaptation in negotiation when both parties possess incomplete information.

This paper introduces virtual fixtures into the traditional negotiation mechanism, locally regulating tracking trajectory and impedance parameters in the negotiating phase until the final plan integrates bilateral intentions well. In the strategy, robots convey its task information to humans and offer groups of guide plans for them to choose, on the premise of maximizing the robot’s own profits.

Compared with traditional negotiation strategies, humans adapt to robots easily and show lower cognitive load in the method, while the satisfied plan shows better performance for the whole human-robot system.

In this study, this paper proposes a novel negotiation strategy to facilitate the mutual adaptation of humans and robots in complicated shared tasks, especially when both parties possess incomplete information of tasks.

This study 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. As a use case, a new collaborative testing system for an automated water leak test was designed using an image processing system utilized by the robot.

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.

This paper examines the development of a new application for lightweight robotic systems and provides a suitable process whereby the system was optimized regarding technical, ergonomic and safety-related aspects.

A new automated testing process in combination with a processing algorithm was developed. A modular system suitable for the integration of human–robot collaboration into the assembly line is presented as well.

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 the system. Feasibility studies for a practical implementation are running at the moment.

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.

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.

Collaboration between frontline employees (FLEs) and frontline robots (FLRs) is expected to play a vital role in service delivery in these increasingly disrupted times. Firms are facing the challenge of designing effective FLE-FLR collaborations to enhance customer experience. This paper develops a framework to explore the potential of FLE-FLR collaboration through the lens of interdependence in customer service experience and advances research that specifically focuses on employee-robot team development.

This paper uses a conceptual approach rooted in the interdependence theory, team design, management, robotics and automation literature.

This paper proposes and defines the Frontline employee – Frontline robot interdependence (FLERI) concept based on three structural components of an interdependent relationship – joint goal, joint workflow and joint decision-making authority. It also provides propositions that outline the potential impact of FLERI on customer experience and employee performance, and outline several boundary conditions that could enhance or inhibit those effects.

Managerial insights into designing an employee-robot team in service delivery are provided.

This study is the first to propose a novel conceptual framework (FLERI) that focuses on the notion of human-robot collaboration in service settings.

The purpose of this paper is to introduce a novel device to handle a robot manipulator which can grip large‐size panels. This concept arises from questioning why the glazing task is always performed manually and it is assumed that if the panel is handled by worker's bare hands, the material is lifted by a robot system and can be assembled to a frame easily and intuitively.

This study proposes the intuitive manipulator device (IMD) which can be attached on the panel directly and connected to it with the coordinate of robot end‐effector based on a virtual coordinate of IMD. The virtual coordinate is defined by the detection of the location of the IMD from the robot end‐effector using IR sensor scanning and origin point estimation method. In this study, the robot manipulator system is operated by a combination of the commands of two IMDs to perform the panel assembly test and its aspect of input commands is compared with the previous force‐control based human‐robot cooperative systems.

The proposed system shows the better performance while reducing the frequent force reflection of robot system against an environment and simplifies the instant input source for robot control system. Those are caused by the intuitiveness of visual servoing performed by operators and the minimization of a force control strategy by utilizing the operator's own sensitivity. The proposed system shows the possibility of efficiency improvement and simple mechatronic system to realize the automation of panel assembly task.

The proposed device alternates the expensive 6‐axis F/T sensor system to handle the robot manipulator by using the two 3‐axis load cell and those force/torque combinations. Also, the developed device is portable and can attach on the material anywhere. That is why this system could cover various sizes of materials. This system minimizes the computational load to control the robot system and improves the efficiency of an assembly task based on the human‐robot cooperation strategy.