Task planning in robot groups for problems with implicitly defined scenarios based on finite-state automata technique
S. V. Manko, Sekou Diane, V. M. Lokhin
- 发表年份
- 2017
- 引用次数
- 8
摘要
This paper provides a methodology for planning collective actions of a group of autonomous robots to solve a multi-stage task in a partially determined environment when operation scenario is not known in advance. We describe finite-automata model of the multi-stage problem and propose a planning algorithm for dynamic formation of the scenario and its parallel-sequential execution. The resulting network of finite state machines allows not only to plan actions of the robots, but also to monitor task execution progress in real-time. Experimental results presented in the paper fully confirm the reliability of the proposed approach.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991