Simulating Group Behaviors
supported by NSF, Texas Higher Education Coordinating Board
Jyh-Ming Lien, Samuel Rodriguez, Xinyu Tang, Nancy M. Amato
Project Alumni: O. Burchan Bayazit, Ross T. Sowell, Arnaud Masciotra, Jean-Phillipe Malric

The objective of our research is to develop efficient techniques for simulating group behaviors. We investigate how agents can work cooperatively to perform tasks, plan paths in dynamic environments, or influence another group of agents to locations in an environment. Group behavior can be observed everywhere. For example, birds fly in flocks, fish swim in schools, sheep move as a herd steered by a dog, agents have objectives in a crowd or game simulation, and ants explore until they find a food source relaying the information to other ants.

In our research, we investigate how to plan motion in dynamic/uncertain environments along with integrating adaptive roadmaps with traditional flocking techniques to generate complex global behaviors that are difficult to generate using traditional emergent approaches such as flocking. An adaptive roadmap is a roadmap (graph) containing representative paths in the environment whose edge values can be updated according to information gathered by the flock members. Our shepherding behaviors investigate how one group of agents can influence another group of agents, the herd, to locations in the environment.

	A Framework for Planning Motion in Environments with Moving Obstacles We present a heuristic approach to planning in an environment with moving obstacles. Our approach assumes that the robot has no knowledge of the future trajectory of the moving objects. Our framework also distinguishes between two types of moving objects:hard and soft objects in the environment. We distinguish between the two types of objects in the environment as varying application domains could allow for some collision between moving objects. A Framework for Planning Motion in Environments with Moving Obstacles Publications
	Group Behaviors using Rule-Based Roadmaps The first behavior we study is homing behavior when the goal is to move the flock from a starting position to a goal position. The second behavior we study is exploring. We consider two kinds of exploring, covering and goal searching. Our third behavior is shepherding, where a flock is steered by an outside agent. Finally, Narrow passage demostrates group behaviors that depend on surrounding environment using rule based roadmap. Generation and Evaluation of Roadmap-Based Group Behaviors We study in depth the generation of roadmap-based searching and hiding. We first propose a variety of these behaviors and then show how these behaviors can be evaluated. Group Behaviors using Rule-Based Roadmaps Publications
	Specialized Techniques for Shepherding Behaviors Techniques for a single shepherd Shepherding behaviors are a type of flocking behavior in which outside agents guide or control members of a flock. Shepherding behaviors can be found in various forms in nature. In this work, we investigate ways to simulate these types of behaviors. Techniques for multiple shepherds When the size of the flock gets large or if the flock's behavior makes it difficult to influence, a single shepherd cannot adequately control the flock. In this work, we study how a group of shepherds can work cooperatively without communication to efficiently control the flock.
	Composable Group Behaviors In this research, we investigate techniques to ease the process of generating realistic and complex group behaviors. Moreover, we provide a "learning" framework that allows these behaviors to adapt to new environments and new tasks and that allows users to make modifications easily.

Papers

A Framework for Planning Motion in Environments with Moving Obstacles Can't connect to local MySQL server through socket '/var/lib/mysql/mysql.sock' (2)