Target position estimation, target acquisition, and obstacle avoidance
Estela Bicho, Gregor Schöner
- 发表年份
- 2002
- 引用次数
- 10
摘要
How can low-level autonomous robots with only very simple sensor systems be endowed with cognitive capabilities? Specifically, we consider a system which uses 5 infra-red sensors and 3 light-dependent resistors to acquire targets and avoid obstacles. How can the system be endowed with a continuous representation of target information, complete with subsymbolic memory and a memory decay process? We show that the dynamic approach employed to control the motion of the robot can be extended to the level of representation, if dynamic (neural) fields are used to interpolate sensory information. We show how the system stabilizes the decision, and activates and deactivates memory. Smooth integration of this dynamic target representation with target acquisition and obstacle avoidance is demonstrated.
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