Coordinated Crowd Simulation With Topological Scene Analysis

Wang

Computer Animation & Virtual

et al. 2019

Team formation with realistic crowd simulation behavior is a challenge in computer graphics, multiagent control, and social simulation. In this study, we propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behavior, and action-control planning. In cooperative-task planning, we improve the grid potential field to achieve global path planning for a team. In coordinated-behavior planning, we propose a time-space table to arrange behavior scheduling for a movement. In action-control planning, we combine the gaze-movement angle model and fuzzy logic control to achieve agent action. Our method has several advantages. (1) The hierarchical architecture is guaranteed to match the human decision process from high to low intelligence. (2) The agent plans his behavior only with the local information of his neighbor; the global intelligence of the group emerges from these local interactions.(3) The time-space table fully utilizes three-dimensional information. Our method is verified using crowds of various densities, from sparse to dense, employing quantitative performance measures. The approach is independent of the simulation model and can be extended to other crowd simulation tasks.

Section: Related Workmentioning

confidence: 99%

Hierarchical planning‐based crowd formation

Wang

Computer Animation & Virtual

et al. 2019

“…Most of those agent-based models focused on how to get collision-free trajectories of each agent by predicting other characters' future positions even when they are in a jammed situation [5]. Barnett et al proposed a method that could obtain congestion-free paths for crowds using topological scene analysis techniques [6]. This method was especially useful when we needed a sort of ordered behavior, such as a soldiers' marching scene.…”

Section: Related Workmentioning

confidence: 99%

GPU-based Fast Motion Synthesis of Large Crowds Using Adaptive Multi-Joint Models

Sung

Kim

2019

Symmetry

This paper introduces a GPU (graphics processing unit)-based fast motion synthesis algorithm for a large crowd. The main parts of the algorithms were selecting the most appropriate joint model given adaptive screen-space occupancy of each character and synthesizing motions for the joint model with one or two input motion capture data. The different joint models had a character range from fine-detailed and fully-articulated ones to the most simplified ones. The motion synthesizer, running on a GPU, performed a series of motion blending for each joint of the characters in parallel. For better performance of the motion synthesizer, the GPU maintained a novel cache structure for given speed parameters. Using the high computation power of GPUs, the motion synthesizer could generate arbitrary speeds and orientations for the motions of a vast number of characters. Experiments showed that the proposed algorithm could animate more than 5000 characters in real-time on modest graphics acceleration cards.

Computer Animation & Virtual

“…An adjustment technique was proposed to reduce the undesirable congestion problem . Multiple paths could be used to perform path planning for agents so that the agents can avoid congestion . Furthermore, groups of agents can move consistently to avoid congestion at corners by employing the dynamic navigation field .…”

Section: Related Workmentioning

confidence: 99%

Transporting objects by multiagent cooperation in crowd simulation

Chen

Wong

2018

This paper focuses on simulating agents transporting passive objects in a virtual environment with pedestrians. The agents adopt the pushing manipulation patterns to transport the passive objects. We propose techniques to achieve two kinds of cooperation. First, the agents transport the passive objects to the goal positions. During the transportation process, the agents may adjust their formation to transport the passive objects effectively. Second, the agents avoid collision with each other and passive objects in an unfreezing manner. Experiment results show that our technique avoids the freezing problem while the agents are transporting multiple objects.