Autonomous Environment Recognition by Robotic Manipulators
スポンサーリンク
概要
- 論文の詳細を見る
This paper discusses methods of autonomus environment recognition and action by a robotic manipulator working with dynamic interaction to the enviroment, e.g., assembling. A method automatically recognizes the contacting situation with the work site from the sensor outputs and the robotic manipulator motion. The autonomous recognition then discriminates the constraint conditions at manopulator hand using the self-organizing map that is a kind of unsupervisedlearning of neural networks. The discrimination of the constraint conditions is successfully demonstraed by a numerical simulation of a 3-link SCARA type manipulator. Another is for the cognitive action. Some approaches based on the reinforcement learnin are proposed. They give models of cognitive actions and aproaches to so-called frame problem obstructing efficient learning and action.
- IEEEの論文
- 2001-08-00
IEEE | 論文
- Magnetic and Transport Properties of Nb/PdNi Bilayers
- Supersonic Ion Beam Driven by Permanent-Magnets-Induced Double Layer in an Expanding Plasma
- Surfactant Adsorption on Single-Crystal Silicon Surfaces in TMAH Solution: Orientation-Dependent Adsorption Detected by In Situ Infrared Spectroscopy
- Extended-range FMCW reflectometry using an optical loop with a frequency shifter
- Teachingless spray-painting of sculptured surface by an industrial robot