Manufacturing challenges are driving the move from separated workspaces of either humans or robots towards a close, symbiotic collaboration. Symbiotic Human-Robot Collaboration requires both parties to not only share the same workspace, but to also perform tasks simultaneously. This raises questions of mutual awareness, for which safety is a critical factor. Despite advances regarding safety systems

This paper provides a review of research into using Augmented Reality (AR) and Mixed Reality(MR) for remote collaboration on physical tasks. AR/MR-based remote collaboration on physical tasks has recently become more prominent in academic research and engineering applications. It has great potential in many fields, such as real-time remote medical consultation, education, training, maintenance, remote

To fully disclose potential configurations of parallel mechanisms (PMs) that are performance-comparable to the commercially successful Exechon, a family of one translational two rotational (1T2R) over-constrained Exechon inspired PMs is synthesized through the screw theory. The synthesized PMs are further comparatively analyzed in terms of inverse kinematics, singularity occurrence and reachable workspace

This paper proposes a new calibration method for joint-dependent geometric errors of six-DoF industrial robots. Chebyshev polynomials are adopted to characterize the high-order joint-dependent geometric error model, revealing the impact of strain wave gearing errors and other sources more accurately. This effort also brings higher observability index on condition of an appropriate order. Furthermore

Augmented Reality (AR) has the potential for facilitating the interaction with robots by enhancing the operator’s spatial understanding as well as providing further cognitive support, e.g. in order to make manual programming processes more efficient and provide on-site simulation. However, we consider major issues that prevent a widespread use of AR towards robotics in industries. Initially, the commissioning

Predictive maintenance has been proposed to maximize the overall plant availability of modern manufacturing systems. To this end, research has been conducted mainly on data-driven prognostic techniques for machinery equipment individual components. However, the lack of historical data together with the intricate design of industrial machines, e.g. robots, stimulate the use of advanced methods exploiting

The robotic grasping task persists as a modern industry problem that seeks autonomous, fast implementation, and efficient techniques. Domestic robots are also a reality demanding a delicate and accurate human–machine interaction, with precise robotic grasping and handling. From decades ago, with analytical heuristics, to recent days, with the new deep learning policies, grasping in complex scenarios

Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, in-depth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model. This knowledge-intensity leads to long development times of respective projects, which contradicts the need for timely decision support. Since more and more companies use industrial

Contact force estimation enables robots to physically interact with unknown environments and to work with human operators in a shared workspace. Most heavy-duty industrial robots without built-in force/torque sensors rely on the inverse dynamics for the sensorless force estimation. However, this scheme suffers from the serious model uncertainty induced by the nonnegligible noise in the estimation process

The disassembly process is the main step of dealing with End-Of-Life (EOL) products. This process is carried out mostly manually so far. Manual disassembly is not efficient economically and the robotic systems are not reliable in dealing with complex disassembly operations as they have high-level uncertainty. In this research, a disassembly planning method based on human-robot collaboration is proposed

In this paper we discuss our evolved understanding on the meaning of agile robotics. The lessons learned are concluded from the four years of our participation in ARIAC, the Agile Robotics for Industrial Automation Competition, that we managed to win in 2020. After elaborating on ARIAC tasks, challenges and scoring and their consequences on algorithm design, error handling and software development

The rapid development of information and communication technologies has triggered the proposition and implementation of smart manufacturing paradigms. In this regard, efficient allocation of smart manufacturing services (SMSs) can provide a sustainable manner for promoting cleaner production. Currently, centralized optimization methods have been widely used to complete the optimal allocation of SMSs

Augmented reality (AR)-based programming using the demonstration method has been widely studied. However, studies on AR-based programming for remote robots are lacking because of the limitation of human–computer interaction. This paper proposes an AR-based robot teleoperation system and method using RGB-D imaging and an attitude teaching device. By sending the color and depth images of the remote robot

The approach of Learning from Demonstrations (LfD) can support human operators especially those without much programming experience to control a collaborative robot (cobot) in an intuitive and convenient means. Gaussian Mixture Model and Gaussian Mixture Regression (GMM and GMR) are useful tools for implementing such a LfD approach. However, well-performed GMM/GMR require a series of demonstrations

Five-axis continuous scanning inspection is an emerging technology in measuring free-form surfaces. Compared to the traditional three-axis scanning inspection, the five-axis continuous surface scanning tremendously boosts the inspection efficiency and suffers from less dynamic error due to adopting a special sweep scanning working mode, which lets the super-light and high-speed rotary two-axis probe

A typical manufacturing process consists of a machining (material removal) process followed by an inspection system for the quality checks. Usually these checks are performed at the end of the process and they may also involve removing the part to a dedicated inspection area. This paper presents an innovative perturbation signal based data generation and machine learning approach to build a robust

Production scheduling plays an important role in the intelligent decision support system and intelligent optimization decision technology. In the context of the globalization trend, the current production and management may extend from a single factory to a distributed production network. In this paper, we study the distributed blocking flowshop scheduling problem (DBFSP) that is an important generalization

Dynamic personalized orders demand and uncertain manufacturing resource availability have become the research hotspots of intelligent resource optimization allocation. Currently, the data generated from the manufacturing industry are rapidly expanding. Such data are multi-source, heterogeneous and multi-scale. Transforming the data into knowledge to optimize the allocation between personalized orders

The poor absolute positioning accuracy of industrial robots is the main obstacle for its further application in precision grinding of complex surfaces, such as blisk, blade, etc. Based on the established kinematic error model of a typical industrial robot FANUC M710ic/50, a novel kinematic parameters calibration method is proposed in this paper to improve the absolute positioning accuracy of robot

Obstacle avoidance is a significant skill not only for mobile robots but also for robot manipulators working in unstructured environments. Various algorithms have been proposed to solve off-line planning and on-line adaption problems. However, it is still not able to ensure safety and flexibility in complex scenarios. In this paper, a novel obstacle avoidance algorithm is proposed to improve the robustness

Kinematic error model plays an important role in the kinematic calibration of robot manipulators. In order to guarantee the best calibration result, the error model should meet the requirements of completeness, minimality and continuity. For the conventional serial robots, these issues have been intensively studied and a consensus has been reached during the past decades. However, for parallel manipulators

Together with the trends of mass personalization, flexible robotic applications become more and more popular. Although conventional robotic automation of workpiece manipulation seems to be solved, advanced tasks still need great amount of effort to be reached. In most cases, on-site robot programming methods, which are intuitive and easy to use, are not applicable in flexible scenarios. On the other

To meet the increasingly complex needs of customers, scheduling faces challenges of the high uncertainty of product arrival in customized manufacturing (CM). This paper proposes a semantic-level component-based scheduling method to solve the uncertainty via the integration of the information model and the computation model. In our proposal, we first construct a component-based framework to illustrate

The use of multiple cooperating robotic manipulators to assemble large aircraft structures entails the scheduling of many discrete tasks such as drilling holes and installing fasteners. Since the tasks have different tool requirements, it is desirable to minimize tool changes that incur significant time costs. We approach this problem as a multi-robot task allocation problem with precedence constraints

Mobile robot machining provides more flexible machining mode compared to the robot machining with a fixed base. However, its machining accuracy is frequently questioned. This paper focuses on the accuracy analysis in mobile robot machining. To evaluate the machining error qualitatively, the tool center point (TCP) error index is defined as the distance between the TCP and the designed machining point

In the robotic eye-in-hand measurement system, a hand-eye calibration method is essential. From the perspective of 3D reconstruction, this paper first analyzes the influence of the line laser sensor hand-eye calibration error on the 3D reconstructed point clouds error. Based on this, considering the influence of line laser sensor measurement errors and the need for high efficiency and convenience in

Combination of geometric and parametric approaches of kinematic identification is proposed in this article. The experimental strategy is similar to that used in geometric approach wherein each axis of the robot is actuated one after the other. This adds clarity to experimental strategy, which becomes ambiguous while solely using a conventional parametric approach. Therefore it is easier to conduct

The solder paste printing (SPP) is a critical procedure in a surface mount technology (SMT) based assembly line, which is one of the major attributes to the defect of the printed circuit boards (PCBs). The quality of SPP is influenced by multiple factors, such as the squeegee speed, pressure, the stencil separation speed, cleaning frequency, and cleaning profile. During printing, the printer environment

The stencil printing process (SPP) is a critical operation in surface mount technology (SMT) because it contributes to 60% of soldering defects. The complex relationships between solder paste volume transfer efficiency (TE) and the SPP variables make the control of the solder paste volume TE during production a challenging problem. This research aims to optimize the stencil printing parameters in real

While multi-robot cells are being used more often in industry, the problem of work-piece position optimization is still solved using heuristics and the human experience and, in most industrial cases, even a feasible solution takes a considerable amount of trials to be found. Indeed, the optimization of a generic performance index along a path is complex, due to the dimension of the feasible-configuration

Effective Prognostics and Health Management (PHM) for cutting tools during Computerized Numerical Control (CNC) processes can significantly reduce downtime and decrease losses throughout manufacturing processes. In recent years, deep learning algorithms have demonstrated great potentials for PHM. However, the algorithms are still hindered by the challenge of the limited amount data available in practical

Shared Manufacturing is a new mode of social manufacturing based on the principles of a sharing economy. This paper presents a scalable framework for blockchain-based Shared Manufacturing that preserves the transparency and immutability characteristics of transaction records, which is critical to building trust between entities in blockchain-based systems. We define a blockchain-based protocol for

With the intensification of globalization, the competition among various manufacturing enterprises has become increasingly fierce, enterprises are developing in the direction of the product diversification, zero inventory or low inventory, and scheduling in production management has become more complicated. In this paper, machine and workpiece were as objects to study the problem of workshop scheduling

Metal products are susceptible to factors such as cutting force, clamping force and heat in the machining process, resulting in product quality problems, such as geometric deformation and surface defects. The real-time observation and control of product quality are integral to optimizing machining process. Digital twin technologies can be used to monitor and control the quality of products via multi-scale

Cloud Manufacturing Service Composition (CMSC), as one of the key issues of Cloud Manufacturing (CMfg), has already attracted much attention. Existing researches on CMSC mainly focus on the optimization efficiency in ideal conditions, while scarcely focus on how to efficiently reconfigure CMSC when service exceptions occur. Uncertain service exceptions often occur during CMSC's execution in real-life

Consumer markets demonstrate an observable trend towards mass customization. Assembly processes are required to adapt in order to meet the requirements of increased product complexity and constant variant updates. A concept to meet challenges within this trend, is a close collaboration between human workers and robots. Currently, in order to protect human operators, there are barriers and restrictions

With good mobility and high flexibility, the mobile manipulator shows a broad application prospect in the machining of large complex components. In these applications, in order to fully utilize the capabilities of the robot, it is usually necessary to design a series of suitable working positions (i.e. robot's base position) for the mobile manipulator. However, the performance distribution of the robot

This paper presents a human–robot co-working system to be applied to industrial tasks such as the production line of a paint factory. The aim is to optimize the picking task with respect to manual operation in a paint factory. The use of an agile autonomous robot co-worker reduces the time in the picking process of materials, and the reduction of the exposure time to raw materials of the worker improves

In the polishing process, contact force has obvious influence on material removal rate, thus realizing stability and effectiveness of force control is a significant issue for automatic polishing. This paper designs a pneumatic polishing force control system to achieve reliability force control. The system is based on a high speed on/off valve which is controlled by Pulse-Width Modulation (PWM) signals

Models that predict the Frequency Response Function (FRF) of six degree-of-freedom (6-dof) industrial robots used for machining operations such as milling are usually built using Experimental Modal Analysis (EMA) of vibration data obtained from modal impact hammer tests performed at a finite number of points in the robot's workspace corresponding to specific arm configurations. While modal impact hammer

Continuous linear commands are widely executed in computer numerical control (CNC) machining. The tangential discontinuity at the junction of consecutive segments restricts the machining efficiency and deteriorates the surface quality. Corners of linear segments have been successfully blended by inserting parametric splines. There still exists challenges when the common methods are employed in the

We share experiences and lessons learned in participating the annual Agile Robotics for Industrial Automation Competition (ARIAC). ARIAC is a simulation-based competition focusing on pushing the agility of robotic systems for handling industrial pick-and-place challenges. Team RuBot started competing from 2019, placing 2nd place in ARIAC 2019 and 3rd place in ARIAC 2020. The article also discusses

Accuracy problem is one of the most challenging issues for the application of parallel robots in manufacturing industry, and kinematic calibration is a feasible approach to solve it. Although lots of researches have brought up a diversity of calibration methods, there are still rooms for the improvement of the accuracy, efficiency and robustness of these calibration effects. In this paper, an improved

The rapid development of the industrial Internet of Things has promoted manufacturing to develop towards the cyber-physical system, of which highly accurate process recognition plays an important role in achieving proactive monitoring of intelligent manufacturing process. Compared to the traditional handcrafted feature-based method, deep model owns convenience in terms of extracting feature automatically

Key areas of robot agility include methods that increase capability and flexibility of industrial robots and facilitate robot re-tasking. Manual guidance can achieve robot agility effectively, provided that a safe and smooth interaction is guaranteed when the user exerts an external force on the end effector. We approach this by designing an adaptive admittance law that can adjust its parameters to

As an underlying and backbone technology of Bitcoin, Blockchain attracted extensive attention worldwide in recent years due to its unique characteristics of decentralization, openness, immutability, anonymity, etc., which enables it to build a trust basis through recording the point-to-point decentralized transactions in an immutable way via the attached timestamp, thereby improving system efficiency

Open and shared manufacturing factories typically dispose of a limited number of industrial robots and/or other production resources that should be properly allocated to tasks in time for an effective and efficient system performance. In particular, we deal with the dynamic capacitated production planning problem with sequence independent setup costs where quantities of products to manufacture need

Manufacturing and Industrial Robotics have reached a point where to be more useful to small and medium sized manufacturers, the systems must become more agile and must be able to adapt to changes in the environment. This paper describes the process for creating and the lessons learned over multiple years of the Agile Robotics for Industrial Automation Competition (ARIAC) being run by the National Institute

Human–Robot Collaboration (HRC) is a term used to describe tasks in which robots and humans work together to achieve a goal. Unlike traditional industrial robots, collaborative robots need to be adaptive; able to alter their approach to better suit the situation and the needs of the human partner. As traditional programming techniques can struggle with the complexity required, an emerging approach

Cycle time for an assembly line in the automotive industry is a crucial requirement for the overall production rate and business achievements. In a multi-robot station, besides workload distribution, operations sequencing, and robot motions, an important issue is robot coordination. A key aspect, so far neglected, is the robot motion delay due to the implementation of robot coordination scheduling:

Modern aircraft assembly demands assembly cells or machines with higher machining efficiency and accuracy. Thus, a dual-machine drilling and riveting cell is developed in this paper. We firstly discuss its physical design, as well as the automatic drilling and riveting process. With the automatic drilling and riveting cell, drilling and riveting production line of aircraft panels can be expected. The

This paper describes a novel method for robotic gear chamfering called dual-edge chamfering which can facilitate simultaneous chamfering of the two edges of adjacent gear teeth and overcome typical registration errors arising due to the placement of the workpiece in the robot workspace. Deviations of the robot end-effector trajectory when compared to the nominal trajectory due to registration errors

Many small and medium-sized manufacturing enterprises (SMEs) have already implemented enterprise resource planning (ERP) and manufacturing execution system (MES) and began to start the journey of cloud manufacturing; however, the high cost of hardware and software investment, implementation, and maintenance usually hinder SMEs from adopting an advanced planning and scheduling (APS) system. This paper

An approach of Task-Parameterised Learning from Demonstration (TP-LfD) aims at automatically adapting the movements of collaborative robots (cobots) to new settings using knowledge learnt from demonstrated paths. The approach is suitable for encoding complex relations between a cobot and its surrounding, i.e., task-relevant objects. However, further efforts are still required to enhance the intelligence

This paper presents an approach for the trajectory planning of a hybrid machine tool based on vibration error, which aims at determining the optimal location and machining time of a given machining path. Firstly, an elastodynamic model of the hybrid robot is proposed by taking compliance of joints and limbs into account. Then, in order to evaluate vibration error in a typical machining path, two indices

In this article, an optimization method is proposed for the dimensional synthesis of robotic manipulators with limited mobility, i.e. with less than 6 degrees-of-freedom (“DoF”), with a prescribed set of tasks in a constrained environment. Since these manipulators cannot achieve full 6-DoF mobility, they are able to follow only certain paths with prescribed position and orientation in space. While

Trochoidal milling is a popular machining method for slotting operation, as it avoids a full tool-workpiece engagement and hence helps, often significantly, slow down the tool wear, which is particularly a concern in the machining of hard-to-cut materials like titanium alloy. However, as the traditional trochoidal milling method assumes a fixed tool orientation, it can only apply to 2D shaped slots

Efficient service scheduling is an important technique to support collaborative manufacturing platforms such as IoT-enable manufacturing systems and cloud manufacturing. In the past few years, optimization problems for processing services have attracted the most attention of researchers and practitioners in terms of task matching, service selection, and scheduling. Logistics services, as another important