Terrain Navigation Skills and Reasoning

We describe a real-time model of terrain traversal by simulated human agents. Agent navigation includes a variety of simulated sensors, terrain reasoning with behavioral constraints, and detailed simulation of a variety of locomotion techniques. Our Kinematic Locomotion Generation Module (KLOG) generates various terrain navigation skills as well as both rhythmic and non-rhythmic variations of these skills. The terrain navigation skills include curved path walking, lateral or backward stepping, running, and the transitions between walking and running for motion continuity. Locomotion attributes such as pelvis rotation and translation and torso flexion and twist are used to modify the KLOG skills so that realistic looking rhythmic locomotion or non-rhythmic variations, such as ducking under a low hanging branch of a tree, can be achieved. The path through the terrain is incrementally computed by a behavioral reasoning system configuring a behavioral feedback network. A number of sensors acquire information on object range, passageways, obstacles, terrain type, exposure to hostile agents and so on. The behavioral reasoner weighs this information along with collision avoidance, cost, danger minimization, locomotion types and other behaviors available to the agent and incrementally attempts to reach a goal location. Since the system is reactive, it can respond to moving obstacles, changing terrain, or unexpected events due to hostile agents or the effects of limited perception

Real-Time Virtual Humans

The last few years have seen great maturation in the computation speed and control methods needed to portray 30 virtual humans suitable for real interactive applications. We first describe the state of the art, then focus on the particular approach taken at the University of Pennsylvania with the Jack system. Various aspects of real-time virtual humans are considered, such as appearance and motion, interactive control, autonomous action, gesture, attention, locomotion, and multiple individuals. The underlying architecture consists of a sense-control-act structure that permits reactive behaviors to be locally adaptive to the environment, and a PaT-Net parallel finite-state machine controller that can be used to drive virtual humans through complex tasks. We then argue for a deep connection between language and animation and describe current efforts in linking them through two systems: the Jack Presenter and the JackMOO extension to lambdaM00. Finally, we outline a Parameterized Action Representation for mediating between language instructions and animated actions

Investigation of an emotional virtual human modelling method

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In order to simulate virtual humans more realistically and enable them life-like behaviours, several exploration research on emotion calculation, synthetic perception, and decision making process have been discussed. A series of sub-modules have been designed and simulation results have been presented with discussion. A visual based synthetic perception system has been proposed in this thesis, which allows virtual humans to detect the surrounding virtual environment through a collision-based synthetic vision system. It enables autonomous virtual humans to change their emotion states according to stimuli in real time. The synthetic perception system also allows virtual humans to remember limited information within their own First-in-first-out short-term virtual memory. The new emotion generation method includes a novel hierarchical emotion structure and a group of emotion calculation equations, which enables virtual humans to perform emotionally in real-time according to their internal and external factors. Emotion calculation equations used in this research were derived from psychologic emotion measurements. Virtual humans can utilise the information in virtual memory and emotion calculation equations to generate their own numerical emotion states within the hierarchical emotion structure. Those emotion states are important internal references for virtual humans to adopt appropriate behaviours and also key cues for their decision making. The work introduces a dynamic emotional motion database structure for virtual human modelling. When developing realistic virtual human behaviours, lots of subjects were motion-captured whilst performing emotional motions with or without intent. The captured motions were endowed to virtual characters and implemented in different virtual scenarios to help evoke and verify design ideas, possible consequences of simulation (such as fire evacuation). This work also introduced simple heuristics theory into decision making process in order to make the virtual human’s decision making more like real human. Emotion values are proposed as a group of the key cues for decision making under the simple heuristic structures. A data interface which connects the emotion calculation and the decision making structure together has also been designed for the simulation system

Investigation of an emotional virtual human modelling method

In order to simulate virtual humans more realistically and enable them life-like behaviours, several exploration research on emotion calculation, synthetic perception, and decision making process have been discussed. A series of sub-modules have been designed and simulation results have been presented with discussion. A visual based synthetic perception system has been proposed in this thesis, which allows virtual humans to detect the surrounding virtual environment through a collision-based synthetic vision system. It enables autonomous virtual humans to change their emotion states according to stimuli in real time. The synthetic perception system also allows virtual humans to remember limited information within their own First-in-first-out short-term virtual memory. The new emotion generation method includes a novel hierarchical emotion structure and a group of emotion calculation equations, which enables virtual humans to perform emotionally in real-time according to their internal and external factors. Emotion calculation equations used in this research were derived from psychologic emotion measurements. Virtual humans can utilise the information in virtual memory and emotion calculation equations to generate their own numerical emotion states within the hierarchical emotion structure. Those emotion states are important internal references for virtual humans to adopt appropriate behaviours and also key cues for their decision making. The work introduces a dynamic emotional motion database structure for virtual human modelling. When developing realistic virtual human behaviours, lots of subjects were motion-captured whilst performing emotional motions with or without intent. The captured motions were endowed to virtual characters and implemented in different virtual scenarios to help evoke and verify design ideas, possible consequences of simulation (such as fire evacuation). This work also introduced simple heuristics theory into decision making process in order to make the virtual human’s decision making more like real human. Emotion values are proposed as a group of the key cues for decision making under the simple heuristic structures. A data interface which connects the emotion calculation and the decision making structure together has also been designed for the simulation system.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Actores sintéticos en tiempo real: Nuevas estructuras de datos y métodos para su integración en aplicaciones de simulación.

RESUMEN La forma más extendida de implementar una aplicación de simulación es mediante la utilización de un grafo de escena. Este tipo de estructura resulta muy adecuado para definir escenas estáticas, pero presenta serias carencias a la hora de representar estructuras articuladas, u objetos con comportamientos complejos. Ambas circunstancias se dan en el caso de los actores virtuales. Este trabajo define nuevas estructuras de datos y métodos que permiten integrar de una forma adecuada actores virtuales en una aplicación de simulación: 1-Se presentan dos nuevos tipos de nodos (Actor y Skeleton), que actúan como elemento modular para la definición y gestión de cualquier tipo de actor virtual. En el diseño de estos nodos se ha prestado especial atención a la estandarización, y la eficiencia computacional. 2-Se proponen técnicas que permiten solventar algunas carencias de los grafos de escena actuales a la hora de ser empleados con actores virtuales. Se actúa sobre el cuello de botella existente en relación con aplicación de matrices de transformación. Se define un nuevo método de gestión de culling específico para actores, es compatible con el tradicional, y actúa sobre los costes asociados a la gestión del comportamiento. Se define un método de gestión de nivel de detalle específico, que actúa simultáneamente sobre la geometría, la topología y el comportamiento, y se realiza un análisis sobre la forma en que los actores han de ser integrados en un sistema multiprocesador 3-Se describe una estructura de nombre ActorClass, que es independiente del grafo de escena y que se encarga de almacenar todas las informaciones de alto nivel que son compartidas por varios actores de la misma especie. Esta estructura es capaz de absorber futuras ampliaciones y permite realizar simulaciones macroscópicas. Con el objeto de demostrar la utilidad práctica de los resultados de este trabajo, se ha implementado una librería de programación y una arquitectura modular que actúan sobre la base de las estructuras y métodos descritos, y se ha desarrollado un ejemplo de su utilización que muestra en detalle todos los aspectos de la integración de actores virtuales en una aplicación de simulación ya existente. ____________________________________________________________________________________________________The Scene Graph is the most widespread method of implementation simulation applications. This kind of structure is a very convenient way to define static scenes, but it has serious drawbacks in representing articulated structures or objects with complex behaviours. Both circumstances are inherent in virtual actors. This thesis defines new data structures and methods permiting the adequate integratión of virtual actors in a simulatión application: 1. Two new kinds of nodes are presented (Actor and Skeleton). These nodes function as modular elements to define and manage all kinds of virtual actor. During the dessing process of this nodes a great attention was paid to standarization and computational efficience. 2. Special techniques are presented in order to solve problems in the current scene graphs: Working on the bottleneck that exists in relation to the transformation matrix process; Defining a new method of culling, specific to actors, that is compatible with the traditional, and considers the costs associated with the behaviour management; Defining a specific Level of Detail method, that works simultaneously with the geometry, the topology and the behaviour; Making an analisis of the technique to ingrate actors in a multiprocessor system. 3. A new structure, named ActorClass, is defined. This structure is independent of the scene graph and is responsible for storing all the high level information that is shared by several actors of the same species. This structure has the capability of assimilating future expansions, and supporting the definition of macroscopic simulations. In order to show the practical utility of the results of this work, a programming library and a modular architecture have been implemented on the basis of these proposed structures and methods. In addition, a practical sample sample has been developed, showing in detail all the aspects of the integratión of virtual actors in an existing simulation application

Terrain reasoning for human locomotion

We describe a real-time model of terrain traver-sal by simulated human agents. Agent navigation zn-cludes a variety of simulated sensors, terrain reason-ing with behavioral constraints, and detailed szmvla-tion of a variety of locomotion techniques. The path through the terrain is incrementally computed by a behavioral reasoning system configuring a behavzoral feedback network. A number of sensors acquire infor-mation on object range, passageways, obstacles, ter-rain type, exposure to hostile agents, azd so on. The behavioral reasoner weighs this informatzon along wzth collision avoidance, cost, danger minimization, loco-motion types, and other behaviors available to the agent and incrementally attempts to reach a goal lo-cation. Since the system is reactive, it can respond to moving obstacles, changing terrazn, or unexpected events due to hostile agents or the effects of limzted percept ion. A mot or- le vel compo ne nt provides general locomotion, including curved path walkzng and runnzng that work in real-time with human figures.