SteerBug: an interactive framework for specifying and detecting steering behaviors.
ABSTRACT The size of crowds that modern computer games and urban simulations are capable of handling has given rise to the challenging problem of debugging and testing massive simulations of autonomous agents. In this paper, we propose SteerBug: an interactive framework for specifying and detecting steering behaviors. Our framework computes a set of time-varying metrics for agents and their environment, which characterize steering behaviors. We identify behaviors of interest by applying conditions (rules) or user defined sketches on the associated metrics. The behaviors we can specify and detect include unnatural steering, plainly incorrect results, or application-specific behaviors of interest. Our framework is extensible and independent of the specifics of any steering approach. To our knowledge, this is the first work that aims to provide a computational framework for specifying and detecting crowd behaviors in animation.
- SourceAvailable from: Nuria Pelechano
Conference Proceeding: Controlling individual agents in high-density crowd simulation.[show abstract] [hide abstract]
ABSTRACT: Simulating the motion of realistic, large, dense crowds of autonomous agents is still a challenge for the computer graphics community. Typical approaches either resemble particle simulations (where agents lack orientation controls) or are conservative in the range of human motion possible (agents lack psychological state and aren't allowed to 'push' each other). Our HiDAC system (for High-Density Autonomous Crowds) focuses on the problem of simulating the local motion and global wayfinding behaviors of crowds moving in a natural manner within dynamically changing virtual environments. By applying a combination of psychological and geometrical rules with a social and physical forces model, HiDAC exhibits a wide variety of emergent behaviors from agent line formation to pushing behavior and its consequences; relative to the current situation, personalities of the individuals and perceived social density.Proceedings of the 2007 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA 2007, San Diego, California, USA, August 2-4, 2007; 01/2007
- [show abstract] [hide abstract]
ABSTRACT: In commercial software development organizations, increased complexity of products, shortened development cycles, and higher customer expectations of quality have placed a major responsibility on the areas of software debugging, testing, and verification. As this issue of the IBM Systems Journal illustrates, there are exciting improvements in the underlying technology on all three fronts. However, we observe that due to the informal nature of software development as a whole, the prevalent practices in the industry are still immature, even in areas where improved technology exists. In addition, tools that incorporate the more advanced aspects of this technology are not ready for large-scale commercial use. Hence there is reason to hope for significant improvements in this area over the next several years.Ibm Systems Journal 12/2001; 41(1):4-12. · 1.29 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: In a previous paper we generated animated agents and their behavior using a combination of XML and images. The behavior of agents was specified as a finite state machine (FSM) in XML. We used images to determine properties of the world that agents react to. While this approach is very flexible, it can be made much faster by using the power available in modern GPUs. In this paper we implement FSMs as fragment shaders using three kinds of images: world space images, agent space images and FSM table images. We show a simple example and compare performance of CPU and GPU implementations. Then we examine a more complex example involving more maps and two types of agents (predator–prey). Furthermore we explore how to render agents in 3D more efficiently by using a variation on pseudoinstancing.Simulation Modelling Practice and Theory 01/2005; · 1.16 Impact Factor