Avatar locomotion in crowd simulation

ACM Transactions on Graphics, 2006

This paper presents an approach to automatically compute animations for virtual (human-like and robot) characters cooperating to move bulky objects in cluttered environments. The main challenge is to deal with 3D collision avoidance while preserving the believability of the agent's behaviors. To accomplish the coordinated task, a geometric and kinematic decoupling of the system is proposed. This decomposition enables us to plan a collision-free path for a reduced system, then to animate locomotion and grasping behaviors independently, and finally to automatically tune the animation to avoid residual collisions. These three steps are applied consecutively to synthesize an animation. The different techniques used, such as probabilistic path planning, locomotion controllers, inverse kinematics and path planning for closed kinematic chains are explained, and the way to integrate them into a single scheme is described.

First International Workshop on …, 2005

Synthesis Lectures on Visual Computing, 2015

is volume presents novel computational models for representing digital humans and their interactions with other virtual characters and meaningful environments. In this context, we describe efficient algorithms to animate, control, and author human-like agents having their own set of unique capabilities, personalities, and desires. We begin with the lowest level of footstep determination to steer agents in collision-free paths. Steering choices are controlled by navigation in complex environments, including multi-domain planning with dynamically changing situations. Virtual agents are given perceptual capabilities analogous to those of real people, including sound perception, multi-sense attention, and understanding of environment semantics which affect their behavior choices. e roles and impacts of individual attributes, such as memory and personality are explored. e animation challenges of integrating a number of simultaneous behavior and movement demands on an agent are addressed through an open source software system. Finally, the creation of stories and narratives with groups of agents subject to planning and environmental constraints culminates the presentation.

Proceedings IEEE Nonrigid and Articulated Motion Workshop, 1997

The last few years have seen great maturation in the computation speed and control methods needed to portray 3D 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. Finally, we argue for a deep connection between language and animation and describe current efforts in linking them through the JackMOO extension to lambdaMOO.

PsycEXTRA Dataset, 2000

Crowd simulation is an essential component of military training and operations. In this paper, we present an approach for generating 3D visualizations and animations from simulation results in the area of agent-based crowd simulation for military operations. The main contribution is to create a simulation bridge between a federated agent-based crowd simulation architecture and a game engine to drive the visualization and animation of virtual crowd in a 3-dimentional space. In our simulation bridge framework, we present a method for data acquisition to create the virtual environment. An interfacing methodology is introduced between the 3D virtual environment maps and the federated agent-based crowd simulator. Our method comprises of converting the 3D maps to multi-level 2D maps to feed the 2D agent-based crowd simulator's virtual world representation. A tool was implemented for defining objects in the virtual environment based on 2D maps and a color coder scheme. Our bridge framework makes use of a game engine as the visualization medium. The 3D virtual environment maps are reconstructed within the game engine and human avatars are created to simulate the agents. Motion, expression and behavioral animations are attached to each virtual agent. At run-time, data is fed from the 2D crowd simulator to our framework via an event-driven file buffer. Virtual agents are created at run-time based on the social aspects of the crowd composition. Behavioral animation is triggered on each agent based on the commands represented in the simulation results. Our framework also provides visualization of emergency situations and makes use of particle dynamics to generate more realistic visuals of disaster situations and human crowd behavior in an emergency situation.

Proceedings of the Artificial Life Conference 2016, 2016

One of the key components of the suspension of disbelief in real-time 3D simulations is the apparent authenticity of actions and gestures played by the individuals of the virtual population. This paper addresses this aspect of simulation, by investigating ways to improve the behavioral realism of virtual humanoid characters in groups and small multitudes. We look at the framework of ALife, identifying and analyzing existing bio-mimicking techniques that can be used in this context and contribute towards the improvement of the plausibility from the generated simulations. By looking at the literature, we identify some of the key elements from ALife that are being progressively incorporated in the simulations of groups and crowds. Then, we discuss a generative model for spontaneity and heterogeneity where bio-inspired agents are individualized with DNA-like strings and appear organized hierarchically exchanging token units of energy, mass, and resources. The result is a generative population of agents that self-organize and interact autonomously, exhibiting interesting social dynamics based on biological tenets and an economy of resources. We analyze this simulation quantitatively with the purpose of studying the impact of each of the previously identified techniques. Figure 1: Global view of the environment of the experimental setting created for this paper.

Computer Graphics Forum, 2004

Crowd simulation for virtual environments offers many challenges centered on the trade-offs between rich behavior, control and computational cost. In this paper we present a new approach to controlling the behavior of agents in a crowd. Our method is scalable in the sense that increasingly complex crowd behaviors can be created without a corresponding increase in the complexity of the agents. Our approach is also more authorable; users can dynamically specify which crowd behaviors happen in various parts of an environment. Finally, the character motion produced by our system is visually convincing. We achieve our aims with a situation-based control structure. Basic agents have very limited behaviors. As they enter new situations, additional, situation-specific behaviors are composed on the fly to enable agents to respond appropriately. The composition is done using a probabilistic mechanism. We demonstrate our system with three environments including a city street and a theater.

Lecture Notes in Computer Science, 2016

Realistic animation of agents' activities in a 3D virtual environment has many useful applications, for examples, creative industries, urban planning, military simulation and disaster management. It is tedious to manually pre-program each agent's actions, its interactions with other agents and with the environment. Simulation is a good approach in this kind of domain since complex global behaviors emerge from the local interactions. We simulate a crowd movement using a multi-agent approach where each agent is situated in the virtual environment. An agent can perceive and interact with other agents and with the environment. Complex behaviors emerging from these interactions are from local rules and without any central control. These behaviors reveal the complexity of the domain without explicitly programming the system. In this work, we investigate (i) the navigation of the agents and (ii) the corresponding animations of each agent's behaviors. Simulation results under different parameters are presented and discussed.