Online robot learning by reward and punishment for a mobile robot

Author

Suwimonteerabuth, Dejvuth ; Chongstitvatana, Prabhas

Author_Institution

Dept. of Comput. Eng., Chulalongkorn Univ., Bangkok, Thailand

Volume

1

fYear

2002

fDate

2002

Firstpage

921

Abstract

The existing robot learning methods require specifically defined goals. We aim to produce a more flexible behavior. We present our work which a human observer can influence the robot behavior. The robot learns by reward and punishment from a human in real-time. To examine the developed approach, we perform a control system for a color-following task as an example. A physical robot is used to perform the experiments. Experimental results show the emergence of learned behaviors. We discussed the factors that influence the learning process.

Keywords

finite state machines; genetic algorithms; image colour analysis; learning (artificial intelligence); mobile robots; optical tracking; real-time systems; robot vision; color following task; feedback; finite-state machine; genetic algorithms; learning from punishment; learning from reward; mobile robot; real-time system; robot learning; Collision avoidance; Control systems; Feedback; Humanoid robots; Humans; Learning systems; Mobile robots; Plastics; Robot control; Robot sensing systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Robots and Systems, 2002. IEEE/RSJ International Conference on

Print_ISBN

0-7803-7398-7

Type

conf

DOI

10.1109/IRDS.2002.1041508

Filename

1041508