A component-based architecture for flexible integration of robotic systems
Min Yang Jung, Anton Deguet, Peter Kazanzides
- 发表年份
- 2010
- 引用次数
- 36
摘要
While a robot control framework generally focuses on real-time performance and efficient data exchange between cooperating tasks or processes, an application such as robot-assisted surgery often demands information from, and integration with, a number of other devices. Thus, the software framework for the integrated system may have different requirements and priorities than a framework for real-time robot control. This paper reports on a component-based architecture that seamlessly bridges the gap between real-time robot control and a distributed, integrated system. The starting point is the cisst library, which provides a component-based framework for lock-free and efficient data exchange between multiple threads within a single process, which is suitable for real-time robot control. This paper describes the extension of the cisst library to support distributed systems, while keeping the same programming model as the single-process, multi-threaded scenario. Thus, application software does not need to know whether the component providing services is within the same process, in a different process, or on a different computer. In comparison, most standard middleware packages support components that fall within the last two categories (different processes on the same computer or different computers). This does not allow them to take advantage of the higher performance that can be achieved using standard lock-free data structures that do not rely on the operating system or on middleware services. Thus, the novelty of this approach is that the same component-based architecture and associated programming model extends from a multi-threaded scenario (which provides the best real-time performance) to a standard multi-process distributed 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