An important prerequisite for determining whether a certain product is producible in any given production facility is an accurate assessment of which production lines and/or the machines are able to execute the necessary production steps. Not only the static information about the capabilities of the machines, but also the conditions of machines and tools are significant for this analysis. Because of the deviation of machine capabilities with increasing deterioration and weary of the equipment, it is also necessary to continuously monitor the status of the machine and analyze the machine conditions. In this paper, we present an approach for generating production plans across multiple factories, considering both static information and dynamic data analysis. Edge devices constantly monitor high frequency machine data and report condensed machine states to an Industrial IoT platform (IIoT). A marketplace within the cloud-application MindSphere enables us to integrate the requirements of the products and the capabilities of the production sites. Customers are be able to evaluate these production plans based on duration, energy consumption, CO2 footprint etc.

Artists explore the visual style of animated characters through 2D concept art, since it affords them a nearly unlimited degree of creative freedom. Realizing the desired visual style, however, within the 3D character animation pipeline is often impossible, since artists must work within the technical limitations of the pipeline toolset. In order to expand the range of possible visual styles for digital characters, our research aims to incorporate the expressiveness afforded by 2D concept painting into the computer animation pipeline as a core component of character authoring and animation. While prior 3D painting methods focus on static geometry or simple animations, we develop tools for the more difficult task of character animation. Our system shows how 3D stroke-based paintings can be deformed using standard rigging tools. We also propose a configuration-space keyframing algorithm for authoring stroke effects that depend on scene variables such as character pose or light position. During animation, our system supports stroke-based temporal keyframing for one-off effects. Our primary technical contribution is a novel interpolation scheme for configuration-space keyframing that ensures smooth, controllable results. We demonstrate several characters authored with our system that exhibit painted effects difficult to achieve with traditional animation tools.

To allow for rapid abstract development of algorithms, model-based tools are often used nowadays. These tools support design using predefined blocks, adaptation using parameters, simulation in a virtual environment and also generation of code for programming embedded devices. However, there is usually no direct connection between the embedded system and the model for programming and runtime control and monitoring. In this paper, we present a seamless tool chain for modelbased algorithm development, simulation and integration on an embedded system as well as runtime control and monitoring from model level. Based on our concept, the development of algorithms can largely be separated from the execution platform and its control and monitoring possibilities. Yet, it is possible to feedback monitored data to support the simulation. The concept is integrated and evaluated and its applicability for the development of an algorithm is demonstrated by means of an example from the field of wireless senor networks localization. We conclude that the outlined approach offers a simple opportunity to reduce development overhead.

We present a method for rendering 3D paintings by compositing brush strokes embedded in space. The challenge in compositing 3D brush strokes is reconciling conflicts between their z -order in 3D and the order in which the strokes were painted, while maintaining temporal and spatial coherence. Our algorithm smoothly transitions between compositing closer strokes over those farther away and compositing strokes painted later over those painted earlier. It is efficient, running in O ( n log n ) time, and simple to implement. We demonstrate its effectiveness on a variety of 3D paintings.

We present a technique to generalize the 2D painting metaphor to 3D that allows the artist to treat the full 3D space as a canvas. Strokes painted in the 2D viewport window must be embedded in 3D space in a way that gives creative freedom to the artist while maintaining an acceptable level of controllability. We address this challenge by proposing a canvas concept defined implicitly by a 3D scalar field. The artist shapes the implicit canvas by creating approximate 3D proxy geometry. An optimization procedure is then used to embed painted strokes in space by satisfying different objective criteria defined on the scalar field. This functionality allows us to implement tools for painting along level set surfaces or across different level sets. Our method gives the power of fine-tuning the implicit canvas to the artist using a unified painting/sculpting metaphor. A sculpting tool can be used to paint into the implicit canvas. Rather than adding color, this tool creates a local change in the scalar field that results in outward or inward protrusions along the field's gradient direction. We address a visibility ambiguity inherent in 3D stroke rendering with a depth offsetting method that is well suited for hardware acceleration. We demonstrate results with a number of 3D paintings that exhibit effects difficult to realize with existing systems.

In this paper a new concept for an infrastructure independent approach to indoor person localization is outlined. It is proposed to deploy an ad-hoc wireless sensor network (WSN) by means of a pedestrian dead reckoning (PDR) unit. The deployed nodes are initialized with a PDR-determined position estimation. Furthermore, a subset of the nodes has a GPS connection and thus an accurate estimation of the own position. Within this infrastructure, persons that carry on-body sensor nodes can then be localized based on received signal strength (RSS) evaluation and extended Kalman filter (EKF) data fusion. An experimental setup with a 65 node ZigBee sensor network is described and the collected data are evaluated off-line. It is analyzed how RSS person localization performs under experimental real-world conditions. The proposed approach results in a localization accuracy on the order of a couple of meters for realistic parameter settings. Initial experiments on node deployment and a simulative evaluation of the influence of biased anchor node position estimations are presented. It is concluded that the proposed system can obtain an accuracy on the order of 3 meters without necessitating map knowledge or previously deployed infrastructure. This accuracy is sufficient for a range of person localization applications.

An important factor for the success of industrial manufacturers is a cost-efficient, robust and thus failsafe production. In this context a topic of increasing interest is the continuous monitoring of machine tools to be able to proactively react to signs of degeneration of single components and ensure the technical availability of the whole plant.

Although animation is one of the most compelling aspects of computer graphics, the possibilities for depicting the movement that make dynamic scenes so exciting remain limited for both still images and animations. In our work, we experiment with motion depiction as a first-class entity within the rendering process. We extend the concept of a surface shader, which is evaluated on an infinitesimal portion of an object's surface at one instant in time, to that of a programmable motion effect, which is evaluated with global knowledge about all portions of an object's surface that pass in front of a pixel during an arbitrary long sequence of time. With this added information, our programmable motion effects can decide to color pixels long after (or long before) an object has passed in front of them. In order to compute the input required by the motion effects, we propose a 4D data structure that aggregates an object's movement into a single geometric representation by sampling an object's position at different time instances and connecting corresponding edges in two adjacent samples with a bilinear patch. We present example motion effects for various styles of speed lines, multiple stroboscopic images, temporal offsetting, and photorealistic and stylized blurring on both simple and production examples.

We present an algorithm that generates natural and intuitive deformations via direct manipulation for a wide range of shape representations and editing scenarios. Our method builds a space deformation represented by a collection of affine transformations organized in a graph structure. One transformation is associated with each graph node and applies a deformation to the nearby space. Positional constraints are specified on the points of an embedded object. As the user manipulates the constraints, a nonlinear minimization problem is solved to find optimal values for the affine transformations. Feature preservation is encoded directly in the objective function by measuring the deviation of each transformation from a true rotation. This algorithm addresses the problem of "embedded deformation" since it deforms space through direct manipulation of objects embedded within it, while preserving the embedded objects' features. We demonstrate our method by editing meshes, polygon soups, mesh animations, and animated particle systems.