Runtime models for automatic reorganization of multi-robot systems
Christopher Zhong, Scott A. DeLoach
- 发表年份
- 2011
- 引用次数
- 25
摘要
This paper presents a reusable framework for developing adaptive multi-robotic systems for heterogeneous robot teams using an organization-based approach. The framework is based on the Organizational Model for Adaptive Computational Systems (OMACS) and the Goal Model for Dynamic Systems (GMoDS). GMoDS is used to capture system-level goals that drive the system. OMACS is an abstract model used to capture the system configuration and allows the team to organize and reorganize without the need for explicit runtime reorganization rules. While OMACS provides an implicit reorganization capability, it also supports policies that can either guide or restrict the resulting organizations thus limiting unexpected or harmful adaptation. We demonstrate our framework by presenting the design and implementation of a multi-robot system for detecting improvised explosive devices. We then highlight the adaptability of the resulting system.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002