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This paper aims to propose a new technique for programming robotized machining tasks based on intuitive human–machine interaction. This will enable operators to create robot programs for small-batch production in a fast and easy way, reducing the required time to accomplish the programming tasks.

This technique makes use of online walk-through path guidance using an external force/torque sensor, and simple and intuitive visual programming, by a demonstration method and symbolic task-level programming.

Thanks to this technique, the operator can easily program robots without learning every robot-specific language and can design new tasks for industrial robots based on manual guidance.

The main contribution of the paper is a new procedure to program machining tasks based on manual guidance (walk-through teaching method) and user-friendly visual programming. Up to now, the acquisition of paths and the task programming were done in separate steps and in separate machines. The authors propose a procedure for using a tablet as the only user interface to acquire paths and to make a program to use this path for machining tasks.

The purpose of this paper is to examine the ability of high-functioning autistic (HFA) children to programme robotic behaviour and sought to elucidate how they describe and construct a robot’s behaviour using iconic programming software.

The robotic learning environment is based on the iPad, an iconic programming app (KinderBot), and EV3. Two case studies, of A. and N., both HFA children of average age 10.5, are the focus of this research.

The research revealed how the participants succeeded in programming the behaviour of an “other” at different programming complexity levels (from simple action to combinations of states of two binary sensors and rule with subroutine). A transformation from procedural to declarative description was also found.

This research on the ability of HFA children to programme robotic behaviour yielded results that can be implemented in K-12 education. Furthermore, learning to programme robots and understand how robotic technologies work may help HFA children to better understand other technology in their environment.

In this research, the authors present an innovative approach that for the first time enables HFA children to “design” the behaviour of smart artefacts to use their sensors to adapt in accordance with the environment. For most HFA children, this would be the first opportunity to “design” the behaviour of the other, as opposed to oneself, since in most of their experience they have been largely controlled by another person.

This paper aims to introduce a generic robot‐programming paradigm for assembly tasks that overcomes the strong coupling between the motion commands and underlying algorithms of programming languages currently on the market. Therefore, it allows an improved method of assembly task programming.

A manipulation primitive (MP) is defined which decouples the programming concept from the algorithms. These primitives can be integrated into existing programming languages and are supported by an intuitive graph‐based language which is introduced in this paper. An open reference architecture to support those primitive‐based programming languages has been designed.

It is possible to describe complex assembly tasks such as manipulation on conveyors or sensor‐integrated compliant motion without abandoning the generality of the programming paradigm. Execution on a reference control system has proven to be successful for several manipulation tasks on different machines.

A complete definition of the MP and a graphical language based on this primitive is given, accompanied by extensive detail information on crucial aspects of the control architecture such as modular trajectory generation, generic interfaces, and real‐time task scheduling.

Presents an approach to improved performance and flexibility in industrial robotics by means of sensor integration and feedback control in task‐level programming and task execution. Also presents feasibility studies in support of the ideas. Discusses some solutions to the problem using six degrees of freedom force control together with the ABB S4CPlus system as an illustrative example. Consider various problems in the design of an open sensor interface for industrial robotics and discusses possible solutions. Finally, presents experimental results from industrial force controlled grinding.

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.

Job analysis is the common basis for designing a training course or programme, preparing performance tests, writing position (job) descriptions, identifying performance appraisal criteria, and job restructuring. Its other applications in human resource development include career counselling and wage and salary administration. Job analysis answers the questions of what tasks, performed in what manner, make up a job. Outputs of this analytical study include: (a) a list of the job tasks; (b) details of how each task is performed; (c) statements describing the responsibility, job knowledge, mental application, and dexterity, as well as accuracy required; and (d) a list of the equipment, materials, and supplies used to perform the job. Various techniques for conducting a job analysis have been used. Each has its advantages and disadvantages. As a result, different techniques or combinations of techniques are appropriate to different situations. The combined on‐site observation and individual interview techniques are recommended for industrial, trade, craft, clerical, and technical jobs because they generate the most thorough and probably the most valid information. A job analysis schedule is used to report the job information obtained through observations and individual interviews. The schedule provides a framework of 12 items in which to arrange and describe important job analysis information. These 12 items are organised into four sections. Section one consists of items one through four. These items identify the job within the establishment in which it occurs. The second section presents item five, the work performed. It provides a thorough and complete description of the tasks of the job. The Work Performed section describes what the job incumbent does, how it is done, and why it is done. Section three presents items six through nine. These are the requirements placed on the job incumbent for successful performance. It is a detailed interpretation of the basic minimum (a) responsibility, (b) job knowledge, (c) mental application, and (d) dexterity and accuracy required of the job incumbent. The fourth section includes three items which provide background information on the job. These items are: (a) equipment, materials and supplies; (b) definitions of terms; and (c) general comments. Appendix A is a glossary of terms associated with job analysis. It is provided to facilitate more exacting communication. A job analysis schedule for a complex and a relatively simple job are included in Appendices B and C. These examples illustrate how important job analysis information is arranged and described. Appendix D provides a list of action verbs which are helpful when describing the manipulative tasks of a job.

A new type of high‐level robot command library is presented, which can be viewed as a marriage between simulation and control. The library commands contain simulations of the physical abilities of the robots as well as having the ability to control the physical machinery. The control of the machinery is performed by translating parameter information and then mapping the library commands to the robot controller commands. To demonstrate the use of the libraries, two robot programming languages have been analysed and new robot command libraries created for two types of machine. The robots selected were a Fanuc A600 and a Unimation PUMA robot. The paper also presents criteria that were used for assessing programming languages for use in programming and controlling robots. The paper shows how simulation can be incorporated into a high‐level robot command library (or object library) and how the command library can be used for the programming of industrial robots. The work has demonstated the advantages of including simulation within robot command libraries. The purpose of the research has not been to define another new robot command library, and the techniques presented here can be applied to other robot languages and high level robot command libraries.

The visual instruction software system was designed with typical industrial situations serving as guidelines. The programmer is assumed to have little knowledge of computers. Rather, he is expected to have a detailed knowledge of the task to be performed. The V/I system provides a safe and simple means to communicate this knowledge to the robot control computer. The design of a software system for programming industrial robots is presented. This software system allows the robot's task to be described through visual means. Television cameras and hand‐held arrays of small lights permit the time spent in programming a robot to be radically reduced. Programmers need only place an array of lights in the robot's field of view and press a button on a hand‐held keyboard to specify robot hand position and orientation. Hence, time delays usually encountered when co‐ordinating the movement of robot arm joints are eliminated.

This paper discusses methodology and technology to aid students learning programming. We have identified and integrated the problem solving and program development skills and knowledge students need to apply when programming with the cognitive activities required to accomplish these tasks. We then developed a composite methodological/software environment that supports the overall process of programming in a manner that gives appropriate weight to both language issues and problem solving. The results of a classroom evaluation of the method and the tool are then presented.

The purpose of this paper is to report a collection of developments that enable users to program industrial robots using speech, several device interfaces, force control and code generation techniques.

The reported system is explained in detail and a few practical examples are given that demonstrate its usefulness for small to medium‐sized enterprises (SMEs), where robots and humans need to cooperate to achieve a common goal (coworker scenario). The paper also explores the user interface software adapted for use by non‐experts.

The programming‐by‐demonstration (PbD) system presented proved to be very efficient with the task of programming entirely new features to an industrial robotic system. The system uses a speech interface for user command, and a force‐controlled guiding system for teaching the robot the details about the task being programmed. With only a small set of implemented robot instructions it was fairly easy to teach the robot system a new task, generate the robot code and execute it immediately.

Although a particular robot controller was used, the system is in many aspects general, since the options adopted are mainly based on standards. It can obviously be implemented with other robot controllers without significant changes. In fact, most of the features were ported to run with Motoman robots with success.

It is important to stress that the robot program built in this section was obtained without writing a single line of code, but instead just by moving the robot to the desired positions and adding the required robot instructions using speech. Even the upload task of the obtained module to the robot controller is commanded by speech, along with its execution/termination. Consequently, teaching the robotic system a new feature is accessible for any type of user with only minor training.

This type of PbD systems will constitute a major advantage for SMEs, since most of those companies do not have the necessary engineering resources to make changes or add new functionalities to their robotic manufacturing systems. Even at the system integrator level these systems are very useful for avoiding the need for specific knowledge about all the controllers with which they work: complexity is hidden beyond the speech interfaces and portable interface devices, with specific and user‐friendly APIs making the connection between the programmer and the system.