David C. Brogan

Animating human athletics

This paper describes algorithms for the animation of male and female models performing three dynamic athletic behaviors: running, bicycling, and vaulting. We animate these behaviors using control algorithms that cause a physically realistic model to perform the desired maneuver. For example, control algorithms allow the simulated humans to maintain balance while moving their arms, to run or bicycle at a variety of speeds, and to perform two vaults. For each simulation, we compare the computed motion to that of humans performing similar maneuvers. We perform the comparison both qualitatively through real and simulated video images and quantitatively through simulated and biomechanical data.

Group Behaviors for Systems with Significant Dynamics

Birds, fish, and many other animals travel as a flock, school, or herd. Animals in these groups must remain in close proximity while avoiding collisions with neighbors and with obstacles. We would like to reproduce this behavior for groups of simulated creatures traveling fast enough that dynamics plays a significant role in determining their movement. In this paper, we describe an algorithm for controlling the movements of creatures that travel as a group and evaluate the performance of the algorithm with three simulated systems: legged robots, humanlike bicycle riders, and point-mass systems. Both the legged robots and the bicyclists are dynamic simulations that must control balance, facing direction, and forward speed as well as position within the group. The simpler point-mass systems are included because they help us to understand the effects of the dynamics on the performance of the algorithm.

Dynamically simulated characters in virtual environments

Animated characters can play the role of teachers or guides, team mates or competitors, or just provide a source of interesting motion in virtual environments. Characters in a compelling virtual environment must have a variety of complex and interesting behaviors, and be responsive to the users actions. The difficulty of constructing such synthetic characters currently hinders the development of these environments, particularly when realism is required. The authors present one approach to populating virtual environments-using dynamic simulation to generate the motion of characters. They explore this approachs effectiveness with two virtual environments: the border collie environment, in which the user acts as a border collie to herd robots into a corral, and the Olympic bicycle race environment, in which the user participates in a bicycle race with synthetic competitors.

Realistic human walking paths

Pedestrian navigation is a complex function of human dynamics, a desired destination, and the presence of obstacles. People cannot stop and start instantaneously and their turning abilities are influenced by kinematic and dynamical constraints. A realistic model of human walking paths is an important development for entertainment applications and many classes of simulations. We present a novel behavioral model of path planning that extends previous models through its significant use of pedestrian performance statistics that were obtained during a suite of experiments. We develop an original interpretation of quantitative metrics for measuring a models accuracy, and use it to compare our path planning approach to a popular contemporary method. Results indicate that this new path planning model better fits natural human behavior than previous models.

Diamond park and spline: Social virtual reality with 3d animation, spoken interaction, and runtime extendability

Diamond Park is a social virtual reality system in which multiple geographically separated users can speak to each other and participate in joint activities. The central theme of the park is cycling. Human visitors to the park are represented by 3D animated avatars and can explore a square mile of 3D terrain. In addition to human visitors, the park hosts a number of computer simulations, including tour buses and autonomous animated figures. Diamond Park is implemented using a software platform called Spline, which makes it easy to build virtual worlds where multiple people interact with each other and with computer simulations in a 3D visual and audio environment. Spline performs all the processing necessary to maintain a distributed, modifiable, and extendable model of a virtual world that is shared between the participants. For more information visit http://www.merl.com.

Group behaviors for systems with significant dynamics

Birds, fish, and many other animals travel as a flock, school, or herd. Animals in these groups must remain in close proximity while avoiding collisions with neighbors and with obstacles. We would like to reproduce this behavior for groups of artificial creatures with significant dynamics. In this paper we describe an algorithm for creatures that move as a group and evaluate the performance of the algorithm with three simulated systems: legged robots, human-like bicycle riders, and point-mass systems. Both the legged robots and the bicyclists are dynamic simulations that must control balance, facing direction, and forward speed as well as movement with the group. The point-mass systems have minimal dynamics and are included to facilitate our understanding of the effects of the dynamics on the performance of the algorithms.

A case study of model context for simulation composability and reusability

How much effort will be required to compose or reuse simulations? What factors need to be considered? It is generally known that composability and reusability are daunting challenges for both simulations and more broadly software design as a whole. We have conducted a small case study in order to clarify the role that model context plays in simulation composability and reusability. For a simple problem: compute the position and velocity of a falling body, we found that a reasonable formulation of a solution included a surprising number of implicit constraints. Equally surprising, in a challenge posed to a small group of capable individuals, no one of them was able to identify more than three-quarters of the ultimate set of validation constraints. We document the challenge, interpret its results, and discuss the utility our study will have in future investigations into simulation composition and reuse.

Approximating component selection

Simulation composability is a difficult capability to achieve due to the challenges of creating components, selecting combinations of components, and integrating the selected components. We address the second of these challenges through analysis of Component Selection (CS), the NP-complete process of selecting a minimal set of components to satisfy a set of objectives. Due to the high order of computational complexity of CS, we examine approximating solutions that make the CS process practicable. We define two variations of CS and prove that good approximations to optimal solutions result from applying a standard Greedy selection algorithm to each. Despite our creation of approximable variations of CS, we conjecture that any proof of the inapproximability of CS will reveal theoretical limitations of its practicality. We conclude that reasonably constrained variations of CS can be solved satisfactorily, and efficiently, but more general cases appear to never be solvable in a similar manner.

Simulation level of detail for multiagent control

Many classes of applications require multiagent navigation control algorithms to specify the movements and actions of heterogeneous groups containing thousands of characters. The scale and complexity of these interacting character groups require navigation control algorithms that are both generalizable and specifically tuned to particular character platforms. We propose a technique called simulation level of detail (LOD) that provides a simulation-based interface between navigation control algorithms and the specific mobile characters on which they operate. A simulation LOD efficiently models a characters ability to move given its dynamic state and provides this simplified version of the character to navigation controllers for use in run-time search algorithms that compute locomotion actions. We develop our simulation LOD algorithms on groups of physically simulated human and alien bicyclists and demonstrate reusable controllers that provide improvements in path following and herding tasks.

The computational complexity of component selection in simulation reuse

Simulation composability has been much more difficult to realize than some initially imagined. We believe that success lies in explicit considerations for the adaptability of components. In this paper, we show that the complexity of optimal component selection for adaptable components is NP-complete. However, our approach allows for the efficient adaptation of components to construct a complex simulation in the most flexible manner while allowing the greatest opportunity to meet all requirements, all the while reducing time and costs. We demonstrate that complexity can vary from polynomial, to NP, and even to exponential as a function of seemingly simple decisions made about the nature of dependencies among components. We generalize these results to show that regardless of the types or reasons for dependencies in component selection, just their mere existence makes this problem very difficult to solve optimally.