Industrial Robotics and the Future of Work

Starting in the 1970s with robots that were physically isolated from contact with their human co-workers, robots now collaborate with human workers towards a common task goal in a shared workspace. This type of robotic device represents a new era of workplace automation. Industrial robotics is rapidly evolving due to advances in sensor technology, artificial intelligence (AI), wireless communications, mechanical engineering, and materials science. While these new robotic devices are used mainly in manufacturing and warehousing, human-robot collaboration is now seen across multiple goods-producing and service-delivery industry sectors. Assessing and controlling the risks of human-robot collaboration is a critical challenge for occupational safety and health research and practice as industrial robotics becomes a pervasive feature of the future of work. Understanding the physical, psychosocial, work organization, and cybersecurity risks associated with the increasing use of robotic technologies is critical to ensuring the safe development and implementation of industrial robotics. This commentary provides a brief review of the uses of robotic technologies across selected industry sectors; the risks of current and future industrial robotic applications for worker and employer alike; strategies for integrating human-robot collaboration into a health and safety management system; and the role of robotic safety standards in the future of work.

Virtual elasto-plastic robot compliance to active environments

Humans exhibit a particular compliant behavior in interactions with their environment. Facilitated by fast physical reasoning, humans are able to rapidly alter their compliance, enhancing robustness and safety in active environments. Transferring these capabilities to robotics is of utmost importance particularly as major space agencies begin investigating the potential of cooperative robotic teams in space. In this scenario, robots in orbit or on planetary surfaces are meant to support astronauts in exploration, maintenance, and habitat building to reduce costs and risks of space missions. A major challenge for interactive robot teams is establishing the capability to act in and interact with dynamic environments. Analogous to humans, the robot should be not only particularly compliant in case of unexpected collisions with other systems but also able to cooperatively handle objects requiring accurate pose estimation and fast trajectory planning. Here, we show that these challenges can be attenuated through an enhancement of active robot compliance introducing a virtual plastic first-order impedance component. We present how elasto-plastic compliance can be realized via energy-based detection of active environments and how evasive motions can be enabled through adaptive plastic compliance. Two space teleoperation experiments using different robotic assets confirm the potential of the method to enhance robustness in interaction with articulated objects and facilitate robot cooperation. An experiment in a health care facility presents how the same method analogously solidifies robotic interactions in human-robot shared environments by giving the robot a subordinate role.

Compliant human-robot object transfer based on modular 3-axis force sensor for collaborative manufacturing

The primary motivation of this paper is to present a compliant and cost-effective solution for object transfer between human and robot. The application prospect of this study is robot-human collaboration in manufacturing. To achieve above goals, a novel modular 3-axis force sensor is proposed for the grasping system to achieve interactive force sensing. Compliant object transfer control strategy, which is composed of incremental force control mode and gravity balance control mode, is proposed for object transfer between human and robot. A prototype of underactuated grasping system which is mounted on the proposed modular 3-axis force sensor is fabricated to investigate the effectiveness of the proposed interactive control strategy. Experimental results reveal that the incremental force control mode is suitable for the lighter objects with a higher interactive sensitivity. For transferring heavier objects, the gravity balance control mode is more suitable. In gravity balance control mode, the human hand could achieve a quasi-static equilibrium with the object, and achieve a compliant transfer operation. Due to the above characteristic, the proposed control strategy has the potentials to enhance the object transfer compliance and safety in the human-robot object transfer process.

Stakeholders’ perspectives on safety-related human–robot collaborative scenarios

Safety plays a key role when implementing collaborative robots (cobots) in human-shared workspace scenarios. Nevertheless, the significance and understanding of safety-related aspects may significantly vary with different stakeholders’ perspectives. In particular, there is often a misconception that cobots are inherently safe with the result of significantly underestimating the need of adopting adequate safety measures and features for the deployment of collaborative robots in industrial and non-industrial frames. Accordingly, this article develops an in-depth analysis of the stakeholders and their stakes in human–robot collaboration in the manufacturing industry with particular attention to the safety aspects. The proposed approach consists of a field study, with an online questionnaire and structured interviews, directed at the main stakeholders. The field study results are presented and compared with insights from two recent explorative studies. Finally, careful analysis and discussion is provided. This research focuses on three topics: (i) the specific phases in the collaborative robot application cycle, (ii) the stakeholders that are involved in each phase, and (iii) the stakes that affect the stakeholders in general, and specifically the role of safety within these stakes. The findings show that awareness of safety issues is still jeopardized between stakeholders. In addition, key stakeholders still significantly underestimate safety-related issues when implementing cobots in new production lines. This implies the need for objective assessment tools that can systematically address and assess all safety-related aspects. This study provides industry practitioners with a broader view of how different stakeholders regard safety-related aspects in the cobot life cycle. This will enable more informed decision-making when implementing cobot solutions and potentially avoid unconsidered safety risks later on. This article also adds to the scant research on the role of each stakeholder in human–robot collaboration.

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.

An Online Distance Tracker for Verification of Robotic Systems' Safety

This paper presents an efficient method for minimum distance calculation between a robot and its environment and the implementation framework as a tool for the verification of robotic systems' safety. Collision is the most fundamental safety problem in robotic systems. Therefore, robotic system software must be verified to ensure that there are no risks of collision during development and implementation. The online distance tracker (ODT) is intended to provide minimum distances between the robots and their environments for verification of system software to inspect whether it causes a collision risk. The proposed method employs the representations of the robot and its environment with cylinders and an occupancy map. Furthermore, the bounding box approach improves the performance of the minimum distance calculation regarding computational cost. Finally, the method is applied to a realistically simulated twin of the ROKOS, which is an automated robotic inspection cell for quality control of automotive body-in-white and is actively used in the bus manufacturing industry. The simulation results demonstrate the feasibility and effectiveness of the proposed method.

Towards safety4.0: A novel approach for flexible human-robot-interaction based on safety-related dynamic finite-state machine with multilayer operation modes

In the era of Industry 4.0 and agile manufacturing, the conventional methodologies for risk assessment, risk reduction, and safety procedures may not fulfill the End-User requirements, especially the SMEs with their product diversity and changeable production lines and processes. This work proposes a novel approach for planning and implementing safe and flexible Human-Robot-Interaction (HRI) workspaces using multilayer HRI operation modes. The collaborative operation modes are grouped in different clusters and categorized at various levels systematically. In addition to that, this work proposes a safety-related finite-state machine for describing the transitions between these modes dynamically and properly. The proposed approach is integrated into a new dynamic risk assessment tool as a promising solution toward a new safety horizon in line with industry 4.0.

Development and Initial Validation of the Safety Training Engagement Scale (STE-S)

Safety training promotes safety at work, in particular through the use of engaging methods. This study introduces a newly developed measure of individual engagement in safety training, and aims to analyze the psychometric proprieties of the scale. The safety training engagement scale (STE) consists of five items pertaining to the trainee’s dedication and absorption in a safety training session. Two studies are carried out to analyze the validity of the scale. The first study focuses on the construct (internal) validity, to examine the scale’s internal consistency and dimensional structure. The second study seeks to provide further evidence for construct validity by testing the external validity of the scale. The sample consists of 913 (study 1) and 133 (study 2) participants in safety training programs in the field of the chemical industry who were invited to fill the STE scale after attending a safety training course. The results provide support to affirm the validity and reliability of the scale. The discussion describes the implication and the limitations of using the STE scale in practical safety training programs, and outlines recommendations for research to improve the scale’s robustness.

Low-Cost Sensory Glove for Human–Robot Collaboration in Advanced Manufacturing Systems

Human–robot collaboration (HRC) enables humans and robots to coexist in the same working environment by performing production operations together. HRC systems are used in advanced manufacturing to improve the productivity and efficiency of a manufacturing process. The question is which HRC systems can ensure that humans can work with robots in a safe environment. This present study proposes a solution through the development of a low-cost sensory glove. This glove was developed using a number of hardware and software tools. The sensory glove analysed and computed the motion and orientation of a worker’s hand. This was carried out to operate the robot through commands and actions while under safe operating conditions. The sensory glove was built as a mechatronic device and was controlled by an algorithm that was designed and developed to compute the data and create a three-dimensional render of the glove as it moved. The image produced enabled the robot to recognize the worker’s hand when collaboration began. Tests were conducted to determine the accuracy, dynamic range and practicality of the system. The results showed that the sensory glove is an innovative low-cost solution for humans and robots to collaborate safely. The sensory glove was able to provide a safe working environment for humans and robots to collaborate on operations together.

Application of an adapted FMEA framework for robot-inclusivity of built environments

Mobile robots are deployed in the built environment at increasing rates. However, lack of considerations for a robot-inclusive planning has led to physical spaces that would potentially pose hazards to robots, and contribute to an overall productivity decline for mobile service robots. This research proposes the use of an adapted Failure Mode and Effects Analysis (FMEA) as a structured tool to evaluate a building's level of robot-inclusivity and safety for service robot deployments. This Robot-Inclusive FMEA (RIFMEA) framework, is used to identify failures in the built environment that compromise the workflow of service robots, assess their effects and causes, and provide recommended actions to alleviate these problems. The method was supported with a case study of deploying telepresence robots in a university campus. The study concluded that common failures were related to poor furniture design, a lack of clearance and hazard indicators, and sub-optimal interior planning.

Assessing effects of exoskeleton misalignment on knee joint load during swing using an instrumented leg simulator

Background

Exoskeletons are working in parallel to the human body and can support human movement by exerting forces through cuffs or straps. They are prone to misalignments caused by simplified joint mechanics and incorrect fit or positioning. Those misalignments are a common safety concern as they can cause undesired interaction forces. However, the exact mechanisms and effects of misalignments on the joint load are not yet known. The aim of this study was therefore to investigate the influence of different directions and magnitudes of exoskeleton misalignment on the internal knee joint forces and torques of an artificial leg.

Methods

An instrumented leg simulator was used to quantify the changes in knee joint load during the swing phase caused by misalignments of a passive knee brace being manually flexed. This was achieved by an experimenter pulling on a rope attached to the distal end of the knee brace to create a flexion torque. The extension was not actuated but achieved through the weight of the instrumented leg simulator. The investigated types of misalignments are a rotation of the brace around the vertical axis and a translation in anteroposterior as well as proximal/distal direction.

Results

The amount of misalignment had a significant effect on several directions of knee joint load in the instrumented leg simulator. In general, load on the knee joint increased with increasing misalignment. Specifically, stronger rotational misalignment led to higher forces in mediolateral direction in the knee joint as well as higher ab-/adduction, flexion and internal/external rotation torques. Stronger anteroposterior translational misalignment led to higher mediolateral knee forces as well as higher abduction and flexion/extension torques. Stronger proximal/distal translational misalignment led to higher posterior and tension/compression forces.

Conclusions

Misalignments of a lower leg exoskeleton can increase internal knee forces and torques during swing to a multiple of those experienced in a well-aligned situation. Despite only taking swing into account, this is supporting the need for carefully considering hazards associated with not only translational but also rotational misalignments during wearable robot development and use. Also, this warrants investigation of misalignment effects in stance, as a target of many exoskeleton applications.

Harnessing robot experimentation to optimize the regulatory framing of emerging robot technologies

From exoskeletons to lightweight robotic suits, wearable robots are changing dynamically and rapidly, challenging the timeliness of laws and regulatory standards that were not prepared for robots that would help wheelchair users walk again. In this context, equipping regulators with technical knowledge on technologies could solve information asymmetries among developers and policymakers and avoid the problem of regulatory disconnection. This article introduces pushing robot development for lawmaking (PROPELLING), an financial support to third parties from the Horizon 2020 EUROBENCH project that explores how robot testing facilities could generate policy-relevant knowledge and support optimized regulations for robot technologies. With ISO 13482:2014 as a case study, PROPELLING investigates how robot testbeds could be used as data generators to improve the regulation for lower-limb exoskeletons. Specifically, the article discusses how robot testbeds could help regulators tackle hazards like fear of falling, instability in collisions, or define the safe scenarios for avoiding any adverse consequences generated by abrupt protective stops. The article’s central point is that testbeds offer a promising setting to bring policymakers closer to research and development to make policies more attuned to societal needs. In this way, these approximations can be harnessed to unravel an optimal regulatory framework for emerging technologies, such as robots and artificial intelligence, based on science and evidence.

Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics

Repetitive industrial tasks can be easily performed by traditional robotic systems. However, many other works require cognitive knowledge that only humans can provide. Human-Robot Collaboration (HRC) emerges as an ideal concept of co-working between a human operator and a robot, representing one of the most significant subjects for human-life improvement.The ultimate goal is to achieve physical interaction, where handing over an object plays a crucial role for an effective task accomplishment. Considerable research work had been developed in this particular field in recent years, where several solutions were already proposed. Nonetheless, some particular issues regarding Human-Robot Collaboration still hold an open path to truly important research improvements. This paper provides a literature overview, defining the HRC concept, enumerating the distinct human-robot communication channels, and discussing the physical interaction that this collaboration entails. Moreover, future challenges for a natural and intuitive collaboration are exposed: the machine must behave like a human especially in the pre-grasping/grasping phases and the handover procedure should be fluent and bidirectional, for an articulated function development. These are the focus of the near future investigation aiming to shed light on the complex combination of predictive and reactive control mechanisms promoting coordination and understanding. Following recent progress in artificial intelligence, learning exploration stand as the key element to allow the generation of coordinated actions and their shaping by experience.

Adaptive Obstacle Avoidance for a Class of Collaborative Robots

In a human–robot collaboration scenario, operator safety is the main problem and must be guaranteed under all conditions. Collision avoidance control techniques are essential to improve operator safety and robot flexibility by preventing impacts that can occur between the robot and humans or with objects inadvertently left within the operational workspace. On this basis, collision avoidance algorithms for moving obstacles are presented in this paper: inspired by algorithms already developed by the authors for planar manipulators, algorithms are adapted for the 6-DOF collaborative manipulators by Universal Robots, and some new contributions are introduced. First, in this work, the safety region wrapping each link of the manipulator assumes a cylindrical shape whose radius varies according to the speed of the colliding obstacle, so that dynamical obstacles are avoided with increased safety regions in order to reduce the risk, whereas fixed obstacles allow us to use smaller safety regions, facilitating the motion of the robot. In addition, three different modalities for the collision avoidance control law are proposed, which differ in the type of motion admitted for the perturbation of the end-effector: the general mode allows for a 6-DOF perturbation, but restrictions can be imposed on the orientation part of the avoidance motion using 4-DOF or 3-DOF modes. In order to demonstrate the effectiveness of the control strategy, simulations with dynamic and fixed obstacles are presented and discussed. Simulations are also used to estimate the required computational effort in order to verify the transferability to a real system.