To this day, most robots are installed behind safety fences, separated from the human. New use-case scenarios demand for collaborative robots, e.g. to assist the human with physically challenging tasks. These robots are mainly installed in work-environments with limited space, e.g. existing production lines. This brings certain challenges for the control of such robots. The presented work addresses a few of these challenges, namely: stable and safe behaviour in contact scenarios; avoidance of restricted workspace areas; prevention of joint limits in automatic mode and manual guidance. The control approach in this paper extents an Energy-aware Impedance controller by repulsive potential fields in order to comply with Cartesian and joint constraints. The presented controller was verified for a KUKA LBR iiwa 7 R800 in simulation as well as on the real robot.

The advent of Industry 4.0 has resulted in a paradigm shift in the role of assembly lines in a manufacturing system. Previously, assembly lines were the central component in bringing about mass production. However, the shift in focus from mass production to mass customization has resulted in several changes to the traditional assembly line. A notable change is the need to create a Digital Twin, which can replicate physical assets, processes and systems that fulfill the various processes in a real world plant. This paper looks at creating a Digital Twin for the optimization of a water bottling plant in a production line. The Digital Twin utilizes an Open Platform Communication server to collect sensor information from the production line through a PLC. Once the Digital Twin has processed the information, the applied solution can then be sent back to the Open Platform Communication server and read in by the individual PLC's to reduce bottlenecks and production delays. This is accomplished by setting up a Digital Twin with three SMART Manufacturing Units that are tasked with the production of 500ml water bottles. Here premade 500ml bottles are fed into the system, filled by the first SMART Manufacturing Unit, capped by the second and thirdly packaged to order. The Digital Twin will be used to analyze the performance of the SMART Manufacturing Units connected in a production line. This performance can then be used as an estimation of how well the physical production line can hope to perform and give an indication of time to market.

This paper defines a framework for virtual recommissioning in reconfigurable manufacturing systems. The need for virtual recommissioning arises with the multiple commissioning tasks in the life span of a reconfigurable manufacturing system. A classification of reconfiguration complexity and elementary abilities are combined in a reconfiguration matrix. The reconfiguration matrix serves as a framework for future research in virtual recommissioning. Lastly a preliminary exploration of virtual recommissioning is conducted on models of an Industry 4.0 Smart Factory demonstrator.

This paper presents the design of Impedance Control to a redundantly actuated Parallel Kinematic Manipulator. The proposed control is based on treating each limb as a single system and their connection through the internal interaction forces. The controller introduces a stiffness and damping matrices that decouples the dynamic behaviour of the robot. Control allocation of torques is applied through an optimization that promotes even distribution of torques over actuators. Simulations showed a good compliance behaviour in low frequencies.

In the rising area of close human-robot collaboration in industrial scenarios, the human operator must be able to easily understand the intent of and data from the robot. Shipbuilding environments exhibit unique features, which make deployment of mobile robots both challenging, relevant, and interesting. One task that is still solely carried out manually today due to its complexity and high need for mobility is the fit-out operation stud welding. This paper presents the latest state-of-the-art developments in human-robot interaction (HRI) for robotic stud welding in large semi-structured manufacturing spaces. The welding itself is carried out autonomously by an autonomous industrial mobile manipulator (AIMM). A novel HRI is proposed, which employs projection mapping and an IMU device to enable intuitive and natural interaction with the robot. Task specific information is projected directly into task space as augmented reality using a projector mounted on the robot end-effector. The IMU device enables non-expert operators to program, verify, and reprogram the robot's task on-site in a ship superstructure. The usability of the system is tested in an extensive user test. It is concluded that non-experts after a short introduction are able to both modify a previous task and instruct and a new task using on average 1:01 and 1:16 minutes. Finally, the HRI has been implemented on a prototype robot and tested in an actual shipyard facility. The precision of the system, including operator inaccuracy, was evaluated to have a standard deviation of 3.6mm.

Trained human co-workers can often easily predict each other's intentions based on prior experience. When collaborating with a robot coworker, however, intentions are hard or impossible to infer. This difficulty of mental introspection makes human-robot collaboration challenging and can lead to dangerous misunderstandings. In this paper, we present a novel, object-aware projection technique that allows robots to visualize task information and intentions on physical objects in the environment. The approach uses modern object tracking methods in order to display information at specific spatial locations taking into account the pose and shape of surrounding objects. As a result, a human co-worker can be informed in a timely manner about the safety of the workspace, the site of next robot manipulation tasks, and next subtasks to perform. A preliminary usability study compares the approach to collaboration approaches based on monitors and printed text. The study indicates that, on average, the user effectiveness and satisfaction is higher with the projection based approach.

Increased customer needs and intensified global competition require intelligent and flexible automation. The interaction technology mobile robotics addresses this, so it holds great potential within the industry. This paper presents the concepts, ideas and working principles of the mobile robot "Little Helper" - an ongoing research project at Aalborg University, Denmark, concerning the development of an autonomous and flexible manufacturing assistant. To demonstrate the "Little Helper" concept a full-scale prototype has been built and experiments carried out. Experiences and knowledge gained from this show promising results regarding industrial integration, exploitation and maturation of mobile robotics.

This paper examines the possibilities of utilizing a virtual environment for programming painting robots. Two cameras are utilized to track the position and movement of the robot programmer and the orientation and position of a spray gun. This data is converted into a virtual environment where a 3D stereo rendering is projected onto a screen for a robot programmer to visualize by use of anaglyph glasses. It is possible to program the paint robot in the virtual world after which the program can be simulated using state of the art graphics processing unit (GPU) programming to create a realtime visualization of the coverage of paint. Results concerning the accuracy and visual examples of the system are given.

Today's industrial automation of spray painting is limited to high part volumes and robot trajectories that are programmed by off-line programming and manual teach-in. This paper presents an approach that uses range image data to obtain the geometry of an unknown part and to automatically generate the robot spray painting trajectories. Laser strip range sensors are installed in front of the paint booth to acquire a range image of the part. Utilizing process knowledge (a geometric library containing constraints specific for the painting application) geometric primitives are detected in the range data. From the geometric primitives a normal vector field is generated that enables to extract main faces. The main faces are located in a 3D space and the process knowledge related to each geometric primitive is utilized to obtain the trajectory for the paint gun. Results of painting a car mirror and steering column are given.