A neural network based real-time robot tracking controller using position sensitive detectors
Hyoung-Gweon Park, Seyoung Oh
- 发表年份
- 2002
- 引用次数
- 4
摘要
A real-time visual servo tracking system for an industrial robot has been developed. The position sensitive detector or PSD, instead of the CCD, is used as a real time vision sensor due to its fast response (The position is converted to analog current). A neural network learns the complex association between the object position and its sensor reading and uses it to track that object. It also turns out that this scheme lends itself to a convenient way to teach a workpath for the robot. Furthermore, for real-time use of the neural net, a novel architecture has been developed based on the concept of input space partitioning and local learning. It exhibits characteristics of fast processing and learning as well as optimal usage of hidden neurons.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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