Operations management issues in design and control of hybrid human-robot collaborative manufacturing systems: a survey

A manufacturing system able to perform a high variety of tasks requires different types of resources. Fully automated systems using robots possess high speed, accuracy, tirelessness, and force, but they are expensive. On the other hand, human workers are intelligent, creative, flexible, and able to work with different tools in different situations. A combination of these resources forms a human-machine/robot (hybrid) system, where humans and robots perform a variety of tasks (manual, automated, and hybrid tasks) in a shared workspace. Contrarily to the existing surveys, this study is dedicated to operations management problems (focusing on the applications and features) for human and machine/robot collaborative systems in manufacturing. This research is divided into two types of interactions between human and automated components in manufacturing and assembly systems: dual resource constrained (DRC) and human-robot collaboration (HRC) optimization problems. Moreover, different characteristics of the workforce and machines/robots such as heterogeneity, homogeneity, ergonomics, and flexibility are introduced. Finally, this paper identifies the optimization challenges and problems for hybrid systems. The existing literature on HRC focuses mainly on the robotic point of view and not on the operations management and optimization aspects. Therefore, the future research directions include the design of models and methods to optimize HRC systems in terms of ergonomics, safety, and throughput. In addition, studying flexibility and reconfigurability in hybrid systems is one of the main research avenues for future research.     

Human–robot interaction in industrial collaborative robotics: a literature review of the decade 2008–2017

ABSTRACT

Currently, a large number of industrial robots have been deployed to replace or assist humans to perform various repetitive and dangerous manufacturing tasks. However, based on current technological capabilities, such robotics field is rapidly evolving so that humans are not only sharing the same workspace with robots, but also are using robots as useful assistants. Consequently, due to this new type of emerging robotic systems, industrial collaborative robots or cobots, human and robot co-workers have been able to work side-by-side as collaborators to accomplish tasks in industrial environments. Therefore, new human–robot interaction systems have been developed for such systems to be able to utilize the capabilities of both humans and robots. Accordingly, this article presents a literature review of major recent works on human–robot interactions in industrial collaborative robots, conducted during the last decade (between 2008 and 2017). Additionally, the article proposes a tentative classification of the content of these works into several categories and sub-categories. Finally, this paper addresses some challenges of industrial collaborative robotics and explores future research issues.     

From Fireflies to Fault-Tolerant Swarms of Robots

One of the essential benefits of swarm robotic systems is redundancy. In case one robot breaks down, another robot can take steps to repair the failed robot or take over the failed robot's task. Although fault tolerance and robustness to individual failures have often been central arguments in favor of swarm robotic systems, few studies have been dedicated to the subject. In this paper, we take inspiration from the synchronized flashing behavior observed in some species of fireflies. We derive a completely decentralized algorithm to detect non-operational robots in a swarm robotic system. Each robot flashes by lighting up its on-board light-emitting diodes (LEDs), and neighboring robots are driven to flash in synchrony. Since robots that are suffering catastrophic failures do not flash periodically, they can be detected by operational robots. We explore the performance of the proposed algorithm both on a real-world swarm robotic system and in simulation. We show that failed robots are detected correctly and in a timely manner, and we show that a system composed of robots with simulated self-repair capabilities can survive relatively high failure rates.      

Introduction to the special issue on Advances in intelligent nonlinear control for robotic systems

In the last two decades, robotic systems have achieved wide applications in every aspect of human society, including industrial manufacturing, automotive production, medical devices, and social lives. With the     

Framework for Assessing Robotic Dexterity within Flexible Manufacturing

With growing demand for flexibility in manufacturing processes, interest in dexterous industrial robots is increasing. To facilitate benchmarking, and to assess the suitability of these robots for flexible manufacturing tasks, there is a need to develop new methods of capturing the relevant performance characteristics of industrial robots. This research aims to show that the Boothroyd-Dewhurst (B-D) Design-For-Assembly method, an established method for optimizing manufacturing processes, can be effectively adopted to form the basis of a comprehensive robotic dexterity assessment within flexible manufacturing. A comparative study is conducted which shows that the B-D classification tables offer the most comprehensive solution due to the range of operations and artifacts considered. Building on these tables, a framework is developed for determining the suitability of a robot system within flexible manufacturing operations. In a sample test-case scenario involving a pick-and-place operation, the framework is shown to produce an accurate estimate of robot performance that can be easily compared to human data. The framework establishes a link between manufacturing operations and robot performance metrics, which addresses the current difficulty in robot integration and highlights the framework’s potential for adoption within flexible manufacturing.     

Robotic clusters: Multi-robot systems as computer clusters: A topological map merging demonstration

In most multi-robot systems, an individual robot is not capable of solving computationally hard problems due to lack of high processing power. This paper introduces the novel concept of robotic clusters to empower these systems in their problem solving. A robotic cluster is a group of individual robots which are able to share their processing resources, therefore, the robots can solve difficult problems by using the processing units of other robots. The concept, requirements, characteristics and architecture of robotic clusters are explained and then the problem of “topological map merging” is considered as a case study to describe the details of the presented idea and to evaluate its functionality. Additionally, a new parallel algorithm for solving this problem is developed. The experimental results proved that the robotic clusters remarkably speedup computations in multi-robot systems. The proposed mechanism can be used in many other robotic applications and has the potential to increase the performance of multi-robot systems especially for solving problems that need high processing resources.     

Wearable Robots for Human Underwater Movement Ability Enhancement: A Survey

Underwater robot technology has shown impressive results in applications such as underwater resource detection. For underwater applications that require extremely high flexibility, robots cannot replace skills that require human dexterity yet, and thus humans are often required to directly perform most underwater operations. Wearable robots (exoskeletons) have shown outstanding results in enhancing human movement on land. They are expected to have great potential to enhance human underwater movement. The purpose of this survey is to analyze the state-of-the-art of underwater exoskeletons for human enhancement, and the applications focused on movement assistance while excluding underwater robotic devices that help to keep the temperature and pressure in the range that people can withstand. This work discusses the challenges of existing exoskeletons for human underwater movement assistance, which mainly includes human underwater motion intention perception, underwater exoskeleton modeling and human-cooperative control. Future research should focus on developing novel wearable robotic structures for underwater motion assistance, exploiting advanced sensors and fusion algorithms for human underwater motion intention perception, building up a dynamic model of underwater exoskeletons and exploring human-in-the-loop control for them.      

Controlling gaze with an embodied interactive control architecture

Human-Robot Interaction (HRI) is a growing field of research that targets the development of robots which are easy to operate, more engaging and more entertaining. Natural human-like behavior is considered by many researchers as an important target of HRI. Research in Human-Human communications revealed that gaze control is one of the major interactive behaviors used by humans in close encounters. Human-like gaze control is then one of the important behaviors that a robot should have in order to provide natural interactions with human partners. To develop human-like natural gaze control that can integrate easily with other behaviors of the robot, a flexible robotic architecture is needed. Most robotic architectures available were developed with autonomous robots in mind. Although robots developed for HRI are usually autonomous, their autonomy is combined with interactivity, which adds more challenges on the design of the robotic architectures supporting them. This paper reports the development and evaluation of two gaze controllers using a new cross-platform robotic architecture for HRI applications called EICA (The Embodied Interactive Control Architecture), that was designed to meet those challenges emphasizing how low level attention focusing and action integration are implemented. Evaluation of the gaze controllers revealed human-like behavior in terms of mutual attention, gaze toward partner, and mutual gaze. The paper also reports a novel Floating Point Genetic Algorithm (FPGA) for learning the parameters of various processes of the gaze controller.     

Describing Upper-Body Motions Based on Labanotation for Learning-from-Observation Robots

We have been developing a paradigm that we call learning-from-observation for a robot to automatically acquire a robot program to conduct a series of operations, or for a robot to understand what to do, through observing humans performing the same operations. Since a simple mimicking method to repeat exact joint angles or exact end-effector trajectories does not work well because of the kinematic and dynamic differences between a human and a robot, the proposed method employs intermediate symbolic representations, tasks, for conceptually representing what-to-do through observation. These tasks are subsequently mapped to appropriate robot operations depending on the robot hardware. In the present work, task models for upper-body operations of humanoid robots are presented, which are designed on the basis of Labanotation. Given a series of human operations, we first analyze the upper-body motions and extract certain fixed poses from key frames. These key poses are translated into tasks represented by Labanotation symbols. Then, a robot performs the operations corresponding to those task models. Because tasks based on Labanotation are independent of robot hardware, different robots can share the same observation module, and only different task-mapping modules specific to robot hardware are required. The system was implemented and demonstrated that three different robots can automatically mimic human upper-body operations with a satisfactory level of resemblance.     

Biologically inspired design of a parallel actuated humanoid robot

This paper presents the comparison for the role of bi-articular and mono-articular actuators in human and bipedal robot legs, in particular the hip and knee joint, for driving the design of a humanoid robot with inspirations from the biological system. The various constraints driving the design of both systems are also compared. Additional factors particular to robotic system are identified and incorporated in the design process. To do this, a dynamic simulation is used to determine loading conditions and the forces and power produced by each actuator under various arrangements. It is shown that while the design principles of humans and humanoids are similar, other constraints ensure that robots are still merely inspired by humans, and not direct copies. A simple design methodology that captures the complexity and constraints of such a system in this paper is proposed. Finally, a full-size humanoid robot that demonstrates the newfound principle is highlighted.     

Knowledge acquisition through human–robot multimodal interaction

The limited understanding of the surrounding environment still restricts the capabilities of robotic systems in real world applications. Specifically, the acquisition of knowledge about the environment typically relies only on perception, which requires intensive ad hoc training and is not sufficiently reliable in a general setting. In this paper, we aim at integrating new acquisition devices, such as tangible user interfaces, speech technologies and vision-based systems, with established AI methodologies, to present a novel and effective knowledge acquisition approach. A natural interaction paradigm is presented, where humans move within the environment with the robot and easily acquire information by selecting relevant spots, objects, or other relevant landmarks. The synergy between novel interaction technologies and semantic knowledge leverages humans’ cognitive skills to support robots in acquiring and grounding knowledge about the environment; such richer representation can be exploited in the realization of robot autonomous skills for task accomplishment.     

Economic analysis of robotic operations: A case study of a thermal spraying robot

There is growing interest in the industrial applications of computer-integrated manufacturing (CIM) and robotic technology. The economic analysis methods which are currently available to assess the cost effectiveness of robotic systems are, however, limited. This paper presents a methodology to address this issue. To demonstrate the methodology, a case-study is presented which uses a thermal spraying robot in a rapid tool manufacturing system. The interdependencies between tolerance, robot accuracy, and the probability of a successful spraying operation are demonstrated. The economic effects of using robots in the spraying process are analyzed. Analytical models are developed to estimate the productivity of components without any defects and the improvement in tool life attributable to robotic spraying. The economic analysis method presented in the paper is also applicable to other operations such as robotic assembly and robotic welding.     

Development of CAM system based on industrial robotic servo controller without using robot language

This paper describes the development of a robotic CAM system for an articulated industrial robot RV1A from the view point of robotic servo controller. It is defined here that the CAM system includes an important function which allows an industrial robot to move along cutter location data (CL data) consisting of position and orientation components. In addition, the developed CAM system has a high applicability to other industrial robots whose servo systems are technically opened to end-users. The developed robotic CAM system works as a straightforward interface between a general CAD/CAM and an industrial robot. At the present stage, the relationship between CAD/CAM and industrial robots is not well established compared to NC machine tools that are widely spread in manufacturing industries. The CAM systems for NC machine tools are already established, however, the CAM system for industrial robots has not been sufficiently considered and developed yet. A teaching pendant is generally used to obtain position and orientation data of the arm tip before an industrial robot works. Here, in order to enhance the relationship between a conventional CAD/CAM system and an industrial robot, a simple and straightforward CAM system without using any robot language is developed and implemented. The basic design of the robotic CAM system and the experimental results are presented in this paper.     

Hybrid mission planning with coalition formation

The increase in robotic capabilities and the number of such systems being used has resulted in opportunities for robots to work alongside humans in an increasing number of domains. The current robot control paradigm of one or multiple humans controlling a single robot is not scalable to domains that require large numbers of robots and is infeasible in communications constrained environments. Robots must autonomously plan how to accomplish missions composed of many tasks in complex and dynamic domains; however, mission planning with a large number of robots for such complex missions and domains is intractable. Coalition formation can manage planning problem complexity by allocating the best possible team of robots for each task. A limitation is that simply allocating the best possible team does not guarantee an executable plan can be formulated. However, coupling coalition formation with planning creates novel, domain-independent tools resulting in the best possible teams executing the best possible plans for robots acting in complex domains.     

Evolving controllers for autonomous robot search teams

Deploying autonomous robot teams instead of humans in hazardous search and rescue missions could provide immeasurable benefits. In such operations, rescue workers often face environments where information about the physical conditions is impossible to obtain, which not only hampers the efficiency and effectiveness of the effort, but also places the rescuers in life-threatening situations. These types of risk promote the potential for using robot search teams in place of humans. This article presents the design and implementation of controllers to provide robots with appropriate behavior. The effective utilization of genetic algorithms to evolve controllers for teams of homogeneous autonomous robots for area coverage in search and rescue missions is described, along with a presentation of a robotic simulation program which was designed and developed. The main objective of this study was to contribute to efforts which attempt to implement real-world robotic solutions for search and rescue missions.     

Biomimetic pupils for augmenting eye emulation in humanoid robots

Contemporary approaches in the development of humanoid robots continually neglect holistic nuances, particularly in ocular prosthetic design. The standard solid glass and acrylic eye construction techniques implemented in humanoid robot design present the observer with an inaccurate representation of the natural human eye by utilising hardened synthetic materials which prohibit pupillary dynamics. Precise eye emulation is an essential factor in the development of a greater realistic humanoid robot as misrepresentation in ocular form and function will appear distinctly prevalent during proximity face to face communication as eye contact is the primary form of interpersonal communicative processing. This paper explores a new material approach in the development of a more accurate humanoid robotic eye construction by employing natural compounds similar in structure to that found in the organic human eye to replace the traditional glass and acrylic modelling techniques. Furthermore, this paper identifies a gap in current ocular system design as no robotic eye model can accurately replicate all the natural operations of the human iris simultaneously in reaction to light and emotive responsivity. This paper offers a new system design approach to augment future humanoid robot eye construction towards achieving a greater accurate and naturalistic eye emulation.     

Adaptive fuzzy control of mechanicalbehavior for a two degree-of-freedomrobotic manipulator

Active compliance control of robotic manipulators is useful in making robots perform precision assembly operations. The essential requirement here is mechanical isotropy of the robot end-point. In this paper the problem of how to achieve this kind of mechanical behaviour is considered from aspects of impedance control and fuzzy set theory. The new fuzzy–impedance control law, which is suitable for real-time applications, is proposed for a two degree-of-freedom (2-d.o.f.) robotic manipulator. According to simulation results, the proposed control law can provide approximately isotropic behaviour of the robot end-point in the whole workspace.     

Direct method for updating flexible multibody systems applied to a milling robot

Industrial robots are currently used in light milling operations for their low cost and large workspace compared with CNC machine tools. However, milling robots are prone to vibration instabilities (chatter) and process deviations since they are significantly less stiff than machine tools. As a result, robot dynamic response depends on its posture which represents a major challenge. This paper presents a direct method to update any multibody model, enclosing flexible rotational/translational or virtual joints with minimal tuning. The novel method allows determining the elastic parameters of the model based on a curve fitting of the frequency response functions measured at the tool tip. Fitting is fast and efficient as it occurs in the frequency domain without the need to transform the measured data into the model parameter space. It relies on a genetic algorithm followed by a deterministic procedure to ensure a refined solution of the identified global minimum. The method is firstly demonstrated and validated on a simulated flexible manipulator with three rotational joints. Its multibody model is built using minimal coordinates with known elastic parameters that the method recovers accurately. The new fitting algorithm is eventually applied to an actual industrial robot (KUKA KR90 R3100 robotic arm) resulting in the proper fit of its critical resonances. Posture dependency can also be tackled by considering multiple measurements in different poses within the same fitting procedure. Updating procedure was programmed in Matlab and made public so that it can be easily adapted to identify elastic parameters of other flexible mechanical systems.