Our paper introducing A VR Prototype for One-Dimensional Movement Visualizations for Robotic Arms, has been accepted for The 7th International Workshop on Virtual, Augmented, and Mixed-Reality for Human-Robot Interactions.

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We present History in Motion (HiM), an interactive visualization tool that enables CAD designers to interactively explore the design history of 3D CAD models. In contrast to manually exploring the modeling history of a CAD project, HiM finds relevant modeling features for geometry elements selected by the designer. We contribute a novel 3D interactive animation that visualizes how the modeling features interact, and are used on top of the CAD model, to realize the geometry. A control panel allows for a deeper exploration of the modeling features, with shortcuts for making modifications.

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Currently process engineers are using documents or authoring tools to bring the assembly instructions to the work floor. This is a time-consuming task, as instructions need to be created for each assembly operation. Furthermore, the engineer needs to be familiar with the assembly sequence. To assist the engineer, a tool is developed that i) uses a heuristic based on visibility, part similarity and proximity to semi-automatically determine the assembly sequence from a CAD model and ii) according to the computed sequence generates digital work instructions including visualizations and animations extracted from the CAD model. In essence, the assembly sequence generation works reversely: it determines the order in which components can be removed from the assembly, by evaluating whether the visibility of a component is obstructed by the remaining assembly. The reversed order is then returned as assembly sequence. During this process the engineer can modify the proposed sequence, add annotations and alter the visualizations of the proposed instructions, i.e., images or 3D-animations. We illustrate that the developed tool effectively supports process engineers and speeds up the creation of digital work instructions by some industrial validation cases, e.g., the assembly of a weaving machine.

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Empathic communication allows individuals to perceive and understand the feeling and emotion of the person with whom they are interacting. This could be particularly important during remote collaboration (such as remote assistance or distance learning) to enhance the social and emotional understanding of geographically distributed partners. However, supporting awareness in remote collaboration is very challenging especially when the interaction with the remote parties results in less information that can be communicated than in a physical interaction. We explore the effect of visualization using physiological cues that allow users to interpret emotional behaviors of remote parties with whom they are interacting in real time. The proposed visual representation allows users to infer emotional patterns from physiological cues that can potentially influence their communication approach toward a more aggressive style or maintain passive and peaceful interaction. We conducted a study involving participants who were paired up for a collaborative assessment task, interacting via voice only, videoconference, or a visual representation of the physiological measurements. Participants perceived the usage of our visual representation with higher group cohesiveness than using voice-only interaction. Further analysis shows that the visual representation significantly increases the positive affect score (i.e., participants are perceived to be more alert and demonstrate less distress) during remote collaboration. We discuss the possibilities of the proposed visual representation to support empathic communication during remote collaboration, and the benefits to the remote partners of having positive affect and group cohesiveness.

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