LEARNING
Dynamic neural field as framework for behaviour coordination in mobile robots
Elena Torta, Raymond H. Cuijpers, James F. Juola
- 发表年份
- 2012
- 引用次数
- 4
摘要
Behaviour based navigation frameworks present the need of mechanisms for behaviour coordination. Algorithms inspired by processing principles of the human brain can provide effective solutions to the coordination problem. Here we present the use of the dynamic neural field, a recurrent neural network, as behaviour coordination layer in robotics navigation algorithms. We test the control loop with the humanoid robot NAO in different contexts. Results show that the use of the dynamic neural field allows the generation of context-dependent effective behaviours.
关键词
Artificial neural networkComputer scienceHumanoid robotField (mathematics)Artificial intelligenceContext (archaeology)Mobile robotRoboticsRobotHuman–computer interaction
相关论文
OTHER
📊 26,957 引用
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 引用
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 引用
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 引用
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002