In recent years human-robot collaboration has been an important topic in manufacturing industries. By introducing robots into the same working cell as humans, the advantages of both humans and robots can be utilized. A robot can handle heavy lifting, repetitive and high accuracy tasks while a human can handle tasks that require the flexibility of humans. If a worker is to collaborate with a robot it is important to have an intuitive way of communicating with the robot. Currently, the way of interacting with a robot is through a teaching pendant, where the robot is controlled using buttons or a joystick. However, speech and touch are two communication methods natural to humans, where speech recognition and haptic control technologies can be used to interpret these communication methods. These technologies have been heavily researched in several research areas, including human-robot interaction. However, research of combining these two technologies to achieve a more natural communication in industrial human-robot collaboration is limited. A demonstrator has thus been developed which includes both speech recognition and haptic control technologies to control a collaborative robot from Universal Robots. This demonstrator will function as an experimental platform to further research on how the speech recognition and haptic control can be used in human-robot collaboration. The demonstrator has proven that the two technologies can be integrated with a collaborative industrial robot, where the human and the robot collaborate to assemble a simple car model. The demonstrator has been used in public appearances and a pilot study, which have contributed in further improvements of the demonstrator. Further research will focus on making the communication more intuitive for the human and the demonstrator will be used as the platform for continued research.

The paper proposes a generic approach to assembly planning where individual tasks, with detailed technological content specified by features, must be combined into an optimal assembly plan subject to technological and geometric constraints. To cope with the complexity and variety of the constraints that refer to the overall assembly process, Benders decomposition is applied. The macro-level master problem looks for the optimal sequencing and resource assignment of the tasks, while sub-problem modules ensure plan feasibility on the micro-level from aspects of technology, fixturing, tooling, and collision. Constraints are also dynamically generated for the master problem. The approach is demonstrated in automotive assembly.

The production industry is moving towards the next generation of assembly, which is conducted based on safe and reliable robots working in the same workplace alongside with humans. Focusing on assembly tasks, this paper presents a review of human–robot collaboration research and its classification works. Aside from defining key terms and relations, the paper also proposes means of describing human–robot collaboration that can be relied on during detailed elaboration of solutions. A human–robot collaborative assembly system is developed with a novel and comprehensive structure, and a case study is presented to validate the proposed framework.

Augmented reality is currently a hot research topic within manufacturing and a great potential of the technique is seen. This study aims to increase the knowledge of the adaptation and usability of augmented reality for the training of operators. A new approach of using dynamic information content is proposed that is automatically adjusted to the individual operator and his/her learning progress for increased efficiency and shorter learning times. The approach make use of the concept of expert systems from the field of artificial intelligence for determine the information content on-line. A framework called “Augmented Reality Expert System” (ARES) is developed that combines AR and expert systems. A proof-of-concept evaluation of the framework is presented in the paper and possible future extensions are discussed.

The aim of this paper to give a comprehensive overview of existing techniques and state-of-the-art systems for indoor localization that could be adopted in smart factories of the future. We present different techniques for calculating the position of a moving object using signal transmission and signal measurement, and compare their advantages and disadvantages. The paper also includes a discussion of various localization systems available in the market and compares their most important features. It ends with a discussion of important issues to consider in future work in order to fully implement indoor, real-time localization of operators in the smart factory.

This paper presents a novel system using Augmented Reality and Expert Systems to enhance the quality and efficiency of shop-floor operators. The novel system proposed provides an adaptive tool that facilitates and enhances support on the shop-floor, due to its ability to dynamically customize the instructions displayed, dependent upon the competence of the user. A comparative study has been made between an existing method of quality control instructions at a machining line in an automotive engine plant and this novel system. It has been shown that the new approach outcompetes the existing system, not only in terms of perceived usability but also with respect to two other important shop-floor variables: quality and productivity. Along with previous research, the outcomes of these test cases indicate the value of using Augmented Reality technology to enhance shop-floor operators’ ability to learn and master new tasks.

With augmented reality, virtual information can be overlaid on the real world in order to enhance a human's perception of reality. In this study, we aim to deepen the knowledge of augmented reality in the shop-floor context and analyze its role within smart factories of the future. The study evaluates a number of approaches for realizing augmented reality and discusses advantages and disadvantages of different solutions from a shop-floor operator's perspective. The evaluation is done in collaboration with industrial companies, including Volvo Cars and Volvo GTO amongst others. The study also identifies important future research directions for utilizing the full potential of the technology and successfully implement it on industrial shop-floors.

In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works.

The paper proposes a generic approach to automated robotic assembly process planning. Such a novel feature-based model of the assembly process is presented which can be synthesized from the standard CAD model of the product and the description of the applicable resources. As a first step towards automated planning, the paper focuses on generating constraints that ensure plan feasibility, as well as on the formal verification of fully specified plans. Examples are given from the domains of robotic remote laser welding as well as collaborative human-robot mechanical assembly.

This paper describes a study of using the concept of augmented reality for supporting assembly line workers in carrying out their task optimally. By overlaying virtual information on real world objects – and thereby enhance the human's perception of reality – augmented reality makes it possible to improve the visual guidance to the workers. In the study, a prototype system is developed based on the Oculus Rift platform and evaluated using a simulated assembling task. The main aim is to investigate user acceptance and how this can possible be improved.


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