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The rapid advances in recent years made within the field of fibre optics and opto‐electronics open up new opportunities within many areas.

The purpose of this paper is to analyse teleoperation of an ABB industrial robot with an ABB IRC5 controller. A method to improve motion smoothness and decrease latency using the existing ABB IRC5 robot controller without access to any low-level interface is proposed.

The proposed control algorithm includes a high-level proportional-integral-derivative controller (PID) controller used to dynamically generate reference velocities for different travel ranges of the tool centre point (TCP) of the robot. Communication with the ABB IRC5 controller was performed utilising the ABB PC software development kit. The multitasking feature of the IRC5 controller was used to enhance the communication frequency between the controller and the remote application. Trajectory tracking experiments of a pre-defined three-dimensional trajectory were carried out and the benefits of the proposed algorithm were demonstrated. The robot was intentionally installed on a wobbly table and its vibrations were recorded using a six-degrees-of-freedom force/torque sensor fitted to the tool mounting interface of the robot. The robot vibrations were used as a measure of the smoothness of the tracking movements.

A communication rate of up to 250 Hz between the computer and the controller was established using C# .Net. Experimental results demonstrating the robot TCP, tracking errors and robot vibrations for different control approaches were provided and analysed. It was demonstrated that the proposed approach results in the smoothest motion with tracking errors of < 0.2 mm.

The proposed approach may be employed to produce smooth motion for a remotely operated ABB industrial robot with the existing ABB IRC5 controller. However, to achieve high-bandwidth path following, the inherent latency of the controller must be overcome, for example by utilising a low-level interface. It is particularly useful for applications including a large number of short manipulation segments, which is typical in teleoperation applications.

Using the proposed technique, off-the-shelf industrial robots can be used for research and industrial applications where remote control is required.

Although low-level control interface for industrial robots seems to be the ideal long-term solution for teleoperation applications, the proposed remote control technique allows out-of-the-box ABB industrial robots with IRC5 controllers to achieve high efficiency and manipulation smoothness without requirements of any low-level programming interface.

This paper aims to introduce a new design concept for robotic manipulator driven by the special two degrees of freedom (DOF) joints. Joint as a basic but essential component of the robotic manipulator is analysed emphatically.

The proposed robotic manipulator consists of several two-DOF joints and a rotary joint. Each of the two-DOF joints consists of a cylinder pairs driven by two DC motors and a universal joint (U-joint). Both kinematics of the robotic manipulator and the two-DOF joint are analysed. The influence to output ability of the joint in terms of the scale effect of the inclined plane is analysed in ADAMS simulation software. The contrast between the general and the proposed two-DOF joint is also studied. Finally, a physical prototype of the two-DOF joint is developed for experiments.

The kinematic analysis indicates that the joint can achieve omnidirectional deflection motion at a range of ±50° and the robotic manipulator can reach a similar workspace in comparison to the general robotic manipulator. Based on the kinematic analysis, two special motion modes are proposed to endow the two-DOF joint with better motion capabilities. The contrast simulation results between the general and the proposed two-DOF joints suggest that the proposed joint can perform better in the output ability. The experimental results verify the kinematic analysis and motion ability of the proposed two-DOF joint.

A new design concept of a robotic manipulator has been presented and verified. The complete kinematic analysis of a special two-DOF joint and a seven-DOF robotic manipulator have been resolved and verified. Compared with the general two-DOF joint, the proposed two-DOF joint can perform better in output ability.

In recent years, owing to the rapidly increasing labor costs, the demand for robots in daily services and industrial operations has been increased significantly. For further applications and human–robot interaction in an unstructured open environment, fast and accurate tracking and strong disturbance rejection ability are required. However, utilizing a conventional controller can make it difficult for the robot to meet these demands, and when a robot is required to perform at a high-speed and large range of motion, conventional controllers may not perform effectively or even lead to the instability.

The main idea is to develop the control law by combining the SMC feedback with the ADRC control architecture to improve the robustness and control quality of a conventional SMC controller. The problem is formulated and solved in the framework of ADRC. For better estimation and control performance, a generalized proportional integral observer (GPIO) technique is employed to estimate and compensate for unmodeled dynamics and other unknown time-varying disturbances. And benefiting from the usage of GPIO, a new SMC law can be designed by synthesizing the estimation and its history.

The employed methodology introduced a significant improvement in handling the uncertainties of the system parameters without compromising the nominal system control quality and intuitiveness of the conventional ADRC design. First, the proposed method combines the advantages of the ADRC and SMC method, which achieved the best tracking performance among these controllers. Second, the proposed controller is sufficiently robust to various disturbances and results in smaller tracking errors. Third, the proposed control method is insensitive to control parameters which indicates a good application potential.

High-performance robot tracking control is the basis for further robot applications in open environments and human–robot interfaces, which require high tracking accuracy and strong disturbance rejection. However, both the varied dynamics of the system and rapidly changing nonlinear coupling characteristic significantly increase the control difficulty. The proposed method gives a new replacement of PID controller in robot systems, which does not require an accurate dynamic system model, is insensitive to control parameters and can perform promisingly for response rapidity and steady-state accuracy, as well as in the presence of strong unknown disturbances.

The purpose of this paper is to present a technique for assessing and comparing the static and dynamic performance of three different models of small six-axis industrial robots using a Renishaw XL80 laser interferometer system, a FARO ION laser tracker and a Renishaw QC20-W telescoping ballbar.

Specific test methods are proposed in this work, and each robot has been measured in a similar area of its working envelope. The laser interferometer measurement instrument is used to assess the static positioning performance along three linear and orthogonal paths. The laser tracker is used to assess the contouring performance at different tool center point (TCP) speeds along a triangular tool path, whereas the telescoping ballbar is used to assess the dynamic positioning performance for circular paths at different TCP speeds and trajectory radii.

It is found that the tested robots behave differently, and that the static accuracy of these non-calibrated robots varies between 0.5 and 2.3 mm. On the other hand, results show that these three robots can provide acceptable corner tracking at low TCP speeds. However, a significant overshoot at the corner is observed at high TCP speed for all the robots tested. It was also found that the smallest increment of Cartesian displacement (Cartesian resolution) that can be taken by the tested robots is approximately 50 μm.

The technique used in this paper allows extremely accurate diagnosis of the robot performance, which makes it possible for the robot user to determine whether the robot is in good or bad condition. It can also help the decision-maker to select the most suitable industrial robot to achieve the desired task with minimum cost and specific application ability.

This paper proposed a new method based on the performance verification approach for solving the robot selection problem for flexible manufacturing systems. Furthermore, despite their importance, bidirectional repeatability and Cartesian resolution are never specified by the manufacturers of industrial robots nor are they described in the ISO 9283:1998 guide, and they are rarely the object of performance assessments. In this work, specific tests are performed to check and quantify the bidirectional repeatability and the Cartesian resolution of each robot.

Development of autonomous robot manipulator for human-robot assembly tasks is a key component to reach high effectiveness. In such tasks, the robot real-time object recognition is crucial. In addition, the need for simple and safe teaching techniques need to be considered, because: small size robot manipulators’ presence in everyday life environments is increasing requiring non-expert operators to teach the robot; and in small size applications, the operator has to teach several different motions in a short time.

For object recognition, the authors propose a deep belief neural network (DBNN)-based approach. The captured camera image is used as the input of the DBNN. The DBNN extracts the object features in the intermediate layers. In addition, the authors developed three teaching systems which utilize iPhone; haptic; and Kinect devices.

The object recognition by DBNN is robust for real-time applications. The robot picks up the object required by the user and places it in the target location. Three developed teaching systems are easy to use by non-experienced subjects, and they show different performance in terms of time to complete the task and accuracy.

The proposed method can ease the use of robot manipulators helping non-experienced users completing different assembly tasks.

This work applies DBNN for object recognition and three intuitive systems for teaching robot manipulators.

This paper aims to present a deflection model to improve positional accuracy of industrial robots. Earlier studies have demonstrated the lack of accuracy of heavy-duty robots when exposed to high external forces. One application where the robot is pushed to its limits in terms of forces is friction stir welding (FSW). This process requires the robot to deliver forces of several kilonewtons causing deflections in the robot joints. Especially for robots with serial kinematics, these deflections will result in significant tool deviations, leading to inferior weld quality.

This paper presents a kinematic deflection model, assuming a rigid link and flexible joint serial kinematics robot. As robotic FSW is a process which involves high external loads and a constant welding speed of usually below 50 mm/s, many of the dynamic effects are negligible. The model uses force feedback from a force sensor, embedded on the robot, and predicts the tool deviation, based on the measured external forces. The deviation is fed back to the robot controller and used for online path compensation.

The model is verified by subjecting an FSW tool to an external load and moving it along a path, with and without deviation compensation. The measured tool deviation with compensation was within the allowable tolerance for FSW.

The model can be applied to other robots with a force sensor.

The presented deflection model is based on force feedback and can predict and compensate tool deviations online.

The purpose of this paper is to present a case‐based system for offline automatic programming in robotic assembly production. This system can reuse past learned robot programs to generate programs for new assembly tasks.

The approach used in this paper is case‐based reasoning. The assembly knowledge acquired from the robot program for an assembly task is retained in a case, which is composed of the primitive task description and the corresponding robot program schema. The retained cases are retrieved by matching features of their primitive task descriptions, and are reused to automatically program for new tasks by instantiating their robot program schemata.

A case not only can be reused as a whole, but also can be reused partly by synthesizing different parts of several cases to generate a program for a new task in a variant environment.

The teaching time of robots can be greatly reduced. This helps to introduce robots into small and medium enterprises.

This paper proposes a novel system that can automatically program for assembly tasks in various environments by flexibly reusing past robot programs.

The purpose of this study has been to evaluate the technology of autonomous mobile manipulation in a real world industrial manufacturing environment. The objective has been to obtain experience in the integration with existing equipment and determine key challenges in maturing the technology to a level of readiness suitable for industry. Despite much research within the topic of industrial mobile manipulation, the technology has not yet found its way to the industry. To mature the technology to a level of readiness suitable for industry real-world experience is crucial. This paper reports from such a real-world industrial experiment with two mobile manipulators.

In the experiment, autonomous industrial mobile manipulators are integrated into the actual manufacturing environment of the pump manufacturer Grundfos. The two robots together solve the task of producing rotors; a task constituted by several sub-tasks ranging from logistics to complex assembly. With a total duration of 10 days, the experiment includes workspace adaptation, safety regulations, rapid robot instruction and running production.

With a setup time of less than one day, it was possible to program both robots to perform the production scenario in collaboration. Despite the success, the experiment clearly demonstrated several topics in need of further research before the technology can be made available to the industry: robustness and cycle time, safety investigations and possibly standardization, and robot and workstation re-configurability.

Despite the attention of research around the world, the topic of industrial mobile manipulation has only seen a limited number of real-world integrations. This work reports from a comprehensive integration into a real-world running production and thus reports on the key challenges identified from this integration.

The main objective of this research is to unravel and analyze emergent technologies that are altering and improving the event industry. The study seeks to recognize the most vital technological advancement, uses and effects on event preparation, management and participant experience.

In this study, a narrative literature review method was used to examine emerging technologies in event management.

The research reveals that the emerging technologies examined in the articles affect and transform the event industry differently. Many of these technologies are currently being used in the event industry and are likely to be utilized in the coming years.

Numerous studies in the literature are related to the research field. However, as technology evolves rapidly, it is necessary to repeat studies at regular intervals. This article contributes to the literature by tracking new technological developments in the event industry.