With the help of XR tools, globally dispersed teams can collaborate remotely in shared virtual environments, reducing the costs associated with physical prototypes and travel while benefiting from including stakeholders from various backgrounds in their process. Integrating digital human models in these virtual environments allows for collaborative design interactions and possibilities for performing ergonomic design and assessments. While screen-based tools are the standard for these evaluations, the inclusion of XR tools can augment current screen-based tools to improve the evaluation of ergonomics and the assembleability of components with digital human models. This study describes an implementation model for collaborative assembly simulations, ergonomics assessments, and reviews in a shared virtual environment with XR and screen-based tools. A pilot study with fifteen participants was designed to compare a Swedish/Chinese vehicle manufacturer's approach to simulating and analyzing assembly designs with the collaborative virtual environment model developed. The results show that teams collaborating in a shared virtual environment performed better in user experience, the feeling of presence, and precision when detecting ergonomics and assemblability issues.

Fotorealistische Modellierung von Menschen ist in der Computer Grafik von besonderer Bedeutung, da diese allgegenwärtig in Film- und Computerspiel-Produktionen benötigt wird. Heutige Modellierungs-Software vereinfacht das Generieren realistischer Modelle. Hingegen ist das Erstellen realitätsgetreuer Abbilder real existierender Personen nach wie vor eine anspruchsvolle Aufgabe. Die vorliegende Arbeit adressiert die automatische Modellierung von realen Menschen und die Verfolgung ihrer Bewegung. Ein Skinning-basierter Ansatz wurde gewählt, um effizientes Generieren von Animationen zu ermöglichen. Für gesteigerte Realitätstreue wurde eine artefaktfreie Skinning-Funktion um den Einfluss mehrerer kinematischer Gelenke erweitert. Dies ermöglicht eine große Vielfalt an real wirkenden komplexen Bewegungen. Zum Erstellen eines Personen-spezifischen Modells wird hier ein automatischer, datenbasierter Ansatz vorgeschlagen. Als Eingabedaten werden registrierte, geschlossene Beispiel-Meshes verschiedener Posen genutzt. Um bestmöglich die Trainingsdaten zu approximieren, werden in einer Schleife alle Komponenten des Modells optimiert: Vertices, Gelenke und Skinning-Gewichte. Zwecks Tracking von Sequenzen verrauschter und nur teilweise erfasster 3D Rekonstruktionen wird ein markerfreier modelladaptiver Ansatz vorgestellt. Durch die nicht-parametrische Formulierung werden die Gelenke des generischen initialien Tracking-Modells uneingeschränkt optimiert, als auch die Oberfläche frei deformiert und somit individuelle Eigenheiten des Subjekts extrahiert. Integriertes a priori Wissen über die menschliche Gestalt, extrahiert aus Trainingsdaten, gewährleistet realistische Modellanpassungen. Das resultierende Modell mit Animationsparametern ist darauf optimiert, bestmöglich die Eingabe-Sequenz wiederzugeben. Zusammengefasst ermöglichen die vorgestellten Ansätze realitätsgetreues und automatisches Modellieren von Menschen und damit akkurates Tracking aus 3D Daten. / Photorealistic modeling of humans in computer graphics is of special interest because it is required for modern movie- and computer game productions. Modeling realistic human models is relatively simple with current modeling software, but modeling an existing real person in detail is still a very cumbersome task. This dissertation focuses on realistic and automatic modeling as well as tracking human body motion. A skinning based approach is chosen to support efficient realistic animation. For increased realism, an artifact-free skinning function is enhanced to support blending the influence of multiple kinematic joints. As a result, natural appearance is supported for a wide range of complex motions. To setup a subject-specific model, an automatic and data-driven optimization framework is introduced. Registered, watertight example meshes of different poses are used as input. Using an efficient loop, all components of the animatable model are optimized to closely resemble the training data: vertices, kinematic joints and skinning weights. For the purpose of tracking sequences of noisy, partial 3D observations, a markerless motion capture method with simultaneous detailed model adaptation is proposed. The non-parametric formulation supports free-form deformation of the model’s shape as well as unconstrained adaptation of the kinematic joints, thereby allowing to extract individual peculiarities of the captured subject. Integrated a-prior knowledge on human shape and pose, extracted from training data, ensures that the adapted models maintain a natural and realistic appearance. The result is an animatable model adapted to the captured subject as well as a sequence of animation parameters, faithfully resembling the input data. Altogether, the presented approaches provide realistic and automatic modeling of human characters accurately resembling sequences of 3D input data.

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Conventional ergonomics analysis involves building physical mockups and conducting simulated operations, such that the constraints experienced by the human subjects can be directly observed. The limitations of this approach are that, they are resource intensive, less flexible for testing design variability and difficult to involve large number of subjects to account for population variability and thus, it is a reactive approach. With the advent of computer aided techniques, efforts are on to support ergonomics analysis processes for proactive design approaches. To achieve this, real scenarios are being simulated in virtual environments which include induction of representative human subjects into such envi-ronments and are termed as Digital Human Models (DHMs). The main challenge in the simulation of humans is to obtain the naturalness that is perceived in human interaction with the environment. This naturalness can be achieved by synergetically modeling the physical performance and cognitive aspects of humans in such a way that one aspect caters the requirements posed from the other. But in current DHMs, the various elements in the physical performance aspect are not in line with the requirements of higher level behav¬ioral/cogntive aspects. Towards meeting this objective, the influence of physical performance aspects of humans on achieving naturalness when DHM interacts with the virtual environment has been studied. In this work, the task of ’reach’ has been chosen for studying the influence of kinematic structure, posture modeling and stability aspects on achieving naturalness for both discrete and statistical humans. Also, a framework has been developed to give instructions based on relations between the segments of the body and objects in the environment. Kinematic structure is modeled to simulate the humans with varied dimensions taking care of the change of link fixations necessary for various tasks. The conventional techniques used to define kinematic structures have limitations in resolving the issues that arise due to change in link fixations. In this work a new scheme is developed to effectively handle precedence relationship sand change of configuration of the existing posture whenever link fixations change. The advantage with this new approach is that complex maneuvers which involve different link fixations and multiple fixations at a time can be managed automati¬cally without the user’s intervention. Posture prediction involves estimation of the whole body posture which a human operator is likely to assume while performing a task. It involves finding a configuration satisfy¬ing the constraints like placing the body-segments in preferred locations of the task space and satisfying the relations specified between body segments. There are two main chal¬lenges in this regard; one is achieving naturalness in the predicted postures and the other is minimizing the mathematical complexity involved in finding the real time solutions. A human-specific posture prediction framework is developed which can handle a variety of constraints and realize the natural behavior. The approach is completely geometry based and unlike numerical methods, the solutions involve no matrix inversions. Digital human models (DHMs), both as avatars and agents, need to be controlled to make them manipulate the objects in the virtual world. A relations based description scheme is developed to instruct the DHM to perform the tasks. The descriptions as a set of relations and postures involve simple triplets and quadruplets. As the descriptions constitute only the relations between actors, incorporating different behavior models while executing the relations is feasible through this framework. Static balancing is one of the crucial factors influencing the posture of humans. The stim¬ulus for the static balancing is the body’s self weight and is governed by the location of its point of application, namely the center of mass (COM). The main focus is on determin¬ing suitable locations for COM to infer about the mobility of the segments which supports the human structure in slow motion scenarios. Various geometric conditions necessary for support retaining, altering are deduced and developed strategies for posture transitions for effective task performance while maintaining stability. These conditions are useful in de¬termining the posture transition required to shift the COM from one region to the other and thus the behaviors realized while accomplishing the tasks are realistic. These behaviors are simulated through statically stable walking and sit to stand posture transition. One of the advantages of employing DHMs in virtual simulations is the feasibility of creat¬ing human models with varied dimensions. A comparative study is conducted on different methods based on probabilistic and statistic theory as an alternative to the percentile based approach with a view to answer the questions like ’what percentage of people can success-fully accomplish a certain task’ and ’how well can people perform when they reach a point in the operational space’. The case study is done assuming upper and lower arms of hu¬mans as a two link planar manipulator and their link lengths as random variables. Making use of statistical DHMs, the concept of task dependent boundary manikins is introduced to geometrically characterize the extreme individuals in the given population who would ac-complish the task. Simulations with these manikins would help designers to visualize how differently the extreme individuals would perform the task. All these different aspects of DHM discussed are incorporated in our native DHM developed named ’MAYAMANAV’. Finally this thesis will end with conclusions and future work discussing how these different aspects of DHM discussed can be combined with behavioral models to simulate the human error.

Der Einsatz von digitalen Menschmodellen erlaubt neben einer frühzeitigen ergonomischen Analyse die Gestaltung von Arbeitsprozessen und stellt ein hilfreiches Werkzeug in der Produkt- und Prozessgestaltung dar. Im Rahmen dieses Beitrages soll auf ausgewählte Schwerpunkte der Entwicklung des digitalen Menschmodells „The Smart Virtual Worker“ eingegangen werden. Das Forschungsprojekt soll einen Beitrag zur Lösung, der mit dem demografischen Wandel der Gesellschaft einhergehenden Herausforderungen leisten. Die daraus resultierenden Forschungsschwerpunkte liegen insbesondere in der Einbeziehung von Alterungs- und psychischen Faktoren in die Bewegungsgenerierung des Menschmodells und der Modellierung von Umweltbedingungen. In Umsetzung des Projektes wurde ein erstes Arbeitsszenario erarbeitet, auf dessen Basis die vorgenannten Forschungsaufgaben interdisziplinär gelöst werden sollen.