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For some special manipulators such as the ones work at the space station, nuclear or some other unmanned environments, the overload, collision, vibration, temperature change or release of the internal stress would affect the structural parameters. And thus the operation precision might constantly decrease in long-term use. In these unmanned environments, the unattended manipulators should calibrate itself when they execute high precision operations or proceed self-maintenances. The purpose of this paper is to propose an automatic visual assistant on-line calibration (AVOC) method based on multi-markers.

A camera fixed on the end of the manipulator is used to measure one to three identification points, which forms an unstable multi-sensor eye-in-hand system. A Gaussian motion method which combines the linear quadratic regulator control and extended Kalman filter together is proposed to make the manipulator track the planned trajectories when its inaccurate structural parameters form uncertain motion errors. And a Monte-Carlo method is proposed to form a high precision and stable signal acquisition when the visual system has measurement errors and intermittent signal feedback. An automatic sampling process is adopted to select the optimal measurement points basing on their variances.

Data analysis and experiment results prove the efficiency and feasibility of the method proposed in this paper. With this method, the positioning accuracy is largely promoted from about 2 mm to 0.04–0.05 mm.

Experiments were carried out successfully on a manipulator in a life sciences glove box that will work at the Chinese space station. It is a low cost and efficient manipulator calibration method. The whole autonomic calibration process takes less than 10 min and requires no human intervention. In addition, this method not only can be used in the calibration of other unmanned articulated manipulator that works in deep ocean, nuclear industry or space but also be useful for the maintenance work in modern factories owing a lot of industrial robots.

Nuclear waste tanks need to be cut into pieces before they can be safely disposed of, but the cutting process produces a large amount of aerosols with radiation, which is very harmful to the health of the operator. The purpose of this paper is to establish an intelligent strategy for an integrated robot designed for measurement and cutting, which can accurately identify and cut unknown nuclear waste tanks and realize autonomous precise processing.

A robot system integrating point cloud measurement and plasma cutting is designed in this paper. First, accurate calibration methods for the robot, tool and hand-eye system are established. Second, for eliminating the extremely scattered point cloud caused by metal surface refraction, an omnidirectional octree data structure with 26 vectors is proposed to extract the point cloud model more accurately. Then, a minimum bounding box is calculated for limiting the local area to be cut, the local three-dimensional shape of the nuclear tank is fitted within the bounding box, in which the cutting trajectories and normal vectors are planned accurately.

The cutting precision is verified by changing the tool into a dial indicator in the simulation and the experiment process. The octree data structure with omnidirectional pointing vectors can effectively improve the filtering accuracy of the scattered point cloud. The point cloud filter algorithm combined with the structure calibration methods for the integrated measurement and processing system can ensure the final machining accuracy of the robot.

Aiming at the problems of large measurement noise interference, complex transformations between coordinate systems and difficult accuracy guarantee, this paper proposes structure calibration, point cloud filtering and point cloud-based planning algorithm, which can greatly improve the reliability and accuracy of the system. Simulation and experiment verify the final cutting accuracy of the whole system.

Managing archives using robots rather than people can considerably enhance efficiency, while need to modify the structure of archive shelves or installation tracks. This paper aims to develop a fully automated archive access robot without modification.

First, a mobile navigation chassis and a motion algorithm based on laser ranging and map matching are created for autonomous movement to any of the archives’ locations. Second, because the existing archives are stacked vertically, the bionic manipulator is made to mimic the movement of manual access to the archives, and it is attached to the robot arm’s end to access different layers of archives. In addition, an industrial camera is used to complete barcode identification of the archives and acquire data on their location and thickness. Finally, the archive bin is created to store archives.

The robot can move, identify and access multiple archival copies placed on floors 1–6 and 2–5 cm thick autonomously without modifying the archival repository or using auxiliary devices.

The robot is currently able to navigate, identify and access files placed on different levels. In the future, the speed of the robot’s navigation and the movement of the robot arm could be even faster, while the level of visualization of the robot could be further improved and made more intelligent.

The archive access robot developed by the authors makes it possible for robots to manage archives instead of human, while being cheaper and easier to deploy than existing robots, and has already been tested in the archive storage room of the State Grid maintenance branch in Jiangsu, China, with better results.

The all-in-one archive access robot can replace existing robotic access solutions, promote intelligent management of the archive industry and the construction of unmanned archive repositories and provide ideas for the development of robots for accessing book-like materials.

This study explores the use of robots to identify and access archives without changing archive shelves or installing auxiliary devices. In this way, the robot can be quickly applied to the storage room to improve the efficiency of archive management.

Mixed reality is expanding in the industrial market and several companies in various fields are adapting this set of technologies for various purposes, such as optimizing processes, improving the programming tasks and promoting the interactivity of their products with the users, or even improving teaching or training. Robotics is another area that can benefit from these recent technologies. In fact, most of the current and futuristic robotic applications, namely, the areas related to advanced manufacturing tasks (e.g. additive-manufacturing, collaborative robotics, etc.), require new technics to actually perceive the result of several actions, including programming tasks, anticipate trajectories, visualize the motion and related information, interface with programmers and users and several other human–machine interfaces. Consequently, this paper aims to explain a new concept of human–machine interfaces aiming to improve the interaction between advanced users and industrial robotic work cells.

The presented concept uses two different applications (apps) developed to explore the advanced features of the Microsoft HoloLens device. The objectives of the project reported in this paper are to optimize robot paths, just by allowing the advanced user to adjust the selected path through the mixed reality environment, and create new paths, just by allowing the advanced user to insert points in the mixed reality environment, correct them as needed, connect them using a certain type of motion, parametrize them (in terms of velocity, motion precision, etc.) and command them to the robot controller.

The solutions demonstrated in this paper show how mixed reality can be used to allow users, with limited programming experience, to fully use the robotics fields. They also show clearly that the integration of the mixed reality technology in the current robot systems will be a turning point in reducing the complexity for end-users.

There are two challenges in the developed applications. The first relates to the robot tool identification, which is very sensitive to lighting conditions or to very complex robot tools. This can result in positioning errors when the software shows the path in the mixed reality scene. The paper presents solutions to overcome this problem. Another unattended challenge is associated with handling the robot singularities when adjusting or creating new paths. Ongoing work is concentrated in creating mechanisms that prevent the end-user to create paths that contain unreachable points or paths that are not feasible because of bad motion parameters.

This paper demonstrates the utilization of mixed reality device to improve the tasks of programming and commanding manufacturing work cells based on industrial robots [see video in (Pires et al., 2018)]. As the presented devices and robot cells are the basis for Industry 4.0 objectives, this demonstration has a vast field of application in the near future, positively influencing the way complex applications, that require much close cooperation between humans and machines, are thought, planned and built. The paper presents two different applications fully ready to use in industrial environments. These applications are scientific experiments designed to demonstrate the principles and technologies of mixed reality applied to industrial robotics, namely, for improving the programming task.

Although the HoloLens device opens outstanding new areas for robot command and programming, it is still expensive and somehow heavy for everyday use. Consequently, this opens an opportunity window to combine these devices with other mobile devices, such as tablets and phones, building applications that take advantage of their combined features.

The paper presents two different applications fully ready to use in industrial environments. These applications are scientific experiments designed to demonstrate the principles and technologies of mixed reality applied to industrial robotics, namely, for improving the programming task. The first application is about path visualization, i.e. enables the user to visualize, in a mixed reality environment, any path preplanned for the robot cell. With this feature, the advanced user can follow the robot path, identify problems, associate any difficulty in the final product with a particular issue in the robot paths, anticipate execution problems with impact on the final product quality, etc. This is particularly important for not only advanced applications, but also for cases where the robot path results from a CAD package (in an offline fashion). The second application consists of a graphical path manipulation procedure that allows the advanced user to create and optimize a robot path. Just by exploring this feature, the end-user can adjust any path obtained from any programming method, using the mixed reality approach to guide (visually) the path manipulation procedure. It can also create a completely new path using a process of graphical insertion of point positions and paths into the mixed reality scene. The ideas and implementations of the paper are original and there is no other example in the literature applied to industrial robot programming.

This paper aims to provide a review of the applications of robotic technology in laboratories.

Following a short introduction, this paper discusses a range of key applications for laboratory robots and describes a number of products. Some recent research is considered and brief conclusions are drawn.

This shows that robotic laboratory automation offers a number of key economic and operational benefits and is being used in many procedures, ranging from drug discovery and toxicity testing to forensics and environmental monitoring. An intriguing possibility is the creation of new scientific knowledge by combining robotic systems with artificial intelligence.

This paper illustrates the vital role played by robotic automation in laboratory procedures.

Launched in May, the 10‐member IN FACT project intends to install two flexible assembly machine prototypes by the end of 1990. Jack Hollingum went to investigate.

The British Robot Association annually awards a Travel scholarship. The 1986 winner from Imperial College reports on the first stage of his tour, to Sweden

To ensure the safety of electric power supply, it is necessary to inspect substation equipment. With the dramatic increase in the number of substations, especially indoor substations, intelligent robot inspection has become an important development direction. This paper aims to describe the design of a trackless robot with a robotic arm, which is capable of navigating autonomously and inspecting the equipment in a narrow and complex indoor substation.

A robust four-wheel platform powered by electric motors is used to carry the robot. By fusing multiple-sensor data and visual markers, the robot achieves autonomous movement based on simultaneous localization and mapping. In addition, to accurately obtain the reading of meters located at height or in a narrow space, the robot is equipped with a newly designed visual servo robotic arm.

In practical application, the robot satisfies the requirements of substation inspection, improves work efficiency, saves costs and achieves good results. The robot is also approved by the relevant departments of the State Grid Corporation of China.

After stable operation in a substation for a period of one year, the robot shows high efficiency and stability, meeting the requirements of indoor substation inspection. Meanwhile, the robot greatly promoted the realization of indoor and outdoor integrated substation automatic inspection, and is expected to be further applied in other industrial inspection sites, including mine, tunnel and nuclear power plant.

Due to the complex indoor environment, most of the existing inspection robots are only used outdoors, and there are no good trackless inspection robots for use indoors. The proposed robot is a trackless intelligent inspection robot for use in indoor substations. The robot features a number of important modules, including an autonomous localization and navigation module and a visual servo manipulator module, which can be used in narrow spaces or at height.

Imagine trying to navigate through your environment while looking straight ahead through a narrow tube. These are essentially the conditions the operator of an ROV in teleoperation mode may have to contend with. We hypothesized that controlling ground-based ROVs would be easier if an operator developed an explicit overview of the space in which the ROV was maneuvering. Accordingly, we conducted a study in which we had naive undergraduate participants explore a maze-like virtual desert environment while drawing a map of the area. After completing a 30-min mapping task, participants re-entered the maze to search for and retrieve a target object. The virtual robots and landscape, which had minimal landmarks and a maze of navigable paths (see Fig. 1), were created using CeeBot (see Chadwick, Gillan, Simon, & Pazuchanics, 2004, for a discussion of the CeeBot tool). Maps drawn by participants were rated independently by three raters (graduate psychology students) for the usefulness of the map for navigating the area on a scale from 1 (not at all useful) to 7 (extremely useful). Cronbach's alpha was computed as a consistency estimate of inter-rater reliability at 0.96.

The US National Bureau of Standards recently showed its Automated Manufacturing Research Facility. Advanced techniques and communication developed are aimed to help US industry.