Task-Level Robot Learning

Title: en_US Task-Level Robot Learning
Creator: en_US Aboaf, Eric W.
Date: 2004-10-20T20:11:45Z
Date Available: 2004-10-20T20:11:45Z
Date Issued: en_US 1988-08-01
Identifier: en_US AITR-1079
uri: http://hdl.handle.net/1721.1/6972
Abstract: en_US We are investigating how to program robots so that they learn from experience. Our goal is to develop principled methods of learning that can improve a robot's performance of a wide range of dynamic tasks. We have developed task-level learning that successfully improves a robot's performance of two complex tasks, ball-throwing and juggling. With task- level learning, a robot practices a task, monitors its own performance, and uses that experience to adjust its task-level commands. This learning method serves to complement other approaches, such as model calibration, for improving robot performance.
Extent: 9997518 bytes; 3880924 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-1079