DocumentCode :
426247
Title :
Implementing reinforcement learning in the chaotic KIV model using mobile robot AIBO
Author :
Kozma, Robert ; Muthu, Sangeeta
Author_Institution :
Div. of Comput. Sci., Memphis Univ., TN, USA
Volume :
3
fYear :
2004
fDate :
28 Sept.-2 Oct. 2004
Firstpage :
2337
Abstract :
We use the biologically inspired dynamic neural network architecture KIV to achieve robust goal-oriented navigation in a physical environment with obstacles. KIV operates on the principle of chaotic neurodynamics, in the style of brains. It performs the task of multi-sensory fusion, recognition, and decision-making in real time. We use the Sony AIBO robot to demonstrate the operation of our algorithm. AIBO´s video camera and infra sensors have been complemented with an external camera for monitoring of the robot´s position. The performance of the autonomous system is evaluated using goal-oriented navigation.
Keywords :
chaos; learning (artificial intelligence); mobile robots; neural net architecture; path planning; Sony AIBO robot; chaotic KIV model; chaotic neurodynamics; dynamic neural network architecture; goal-oriented navigation; mobile robot; reinforcement learning; Biological neural networks; Biological system modeling; Cameras; Chaos; Learning; Mobile robots; Navigation; Robot sensing systems; Robot vision systems; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2004. (IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on
Print_ISBN :
0-7803-8463-6
Type :
conf
DOI :
10.1109/IROS.2004.1389758
Filename :
1389758
Link To Document :
بازگشت