Title :
Pushing operation of manipulator based on experience learning: Position prediction of an object and pushing analysis
Author :
Haolin Yang ; Fuchun Sun ; Di Guo
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Abstract :
With the popularization and application of manipulator in the field of industrial production and scientific experiment, it is crucial to focus on the manipulator motion control. Pushing is the basis and assistance of complex operations of manipulator, and research goes on pushing operation has a very important and practical significance. Learning from experience has been recognized as an important cognitive ability in the cognitive architecture, and it makes the manipulator repeat the same or similar task in similar environments. The goal of this paper is to achieve the position prediction of a target object in pushing operation with experience learning and analyze the pushing operation.
Keywords :
image colour analysis; industrial manipulators; learning (artificial intelligence); motion control; robot vision; experience learning; industrial production; manipulator motion control; manipulator pushing operation; object position prediction; pushing analysis; Acceleration; Force; Image resolution; Least squares methods; Manipulators; Neural networks; Training;
Conference_Titel :
Multisensor Fusion and Information Integration for Intelligent Systems (MFI), 2014 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6731-5
DOI :
10.1109/MFI.2014.6997642
