Learning reliable manipulation strategies without initial physical models
- 4 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1224-1230 vol.2
- https://doi.org/10.1109/robot.1990.126165
Abstract
A description is given of a robot, possessing limited sensory and effectory capabilities but no initial model of the effects of its actions on the world, that acquires such a model through exploration, practice, and observation. By acquiring an increasingly correct model of its actions, it generates increasingly successful plans to achieve its goals. In an apparently nondeterministic world, achieving reliability requires the identification of reliable actions and a preference for using such actions. Furthermore, by selecting its training actions carefully, the robot can significantly improve its learning rate.Keywords
This publication has 8 references indexed in Scilit:
- Dynamic world modeling for an intelligent mobile robot using a rotating ultra-sonic ranging devicePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Task-level robot learningPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Automatic discovery of robotic grasp configurationsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- EXPERIMENTS IN ROBOT LEARNINGPublished by Elsevier ,1989
- An exploration of sensorless manipulationIEEE Journal on Robotics and Automation, 1988
- Sensor-based control of robotic manipulators using a general learning algorithmIEEE Journal on Robotics and Automation, 1987
- A self-learning automaton with variable resolution for high precision assembly by industrial robotsIEEE Transactions on Automatic Control, 1982
- Learning Automata - A SurveyIEEE Transactions on Systems, Man, and Cybernetics, 1974