Massachusetts Institute of Technology
Teaching a robot manipulation skills through demonstration
Abstract
dc:description.abstractAn automated software system has been developed to allow robots to learn a generalized motor skill from demonstrations given by a human operator. Data is captured using a teleoperation suit as a task is performed repeatedly on Leonardo, the Robotic Life group's anthropomorphic robot, in different parts of his workspace. Stereo vision and tactile feedback data are also captured. Joint and end effector motions are measured through time, and an improved Mean Squared Velocity [MSV] analysis is performed to segment motions into possible goal-directed streams. Further combinatorial selection of subsets of markers allows final episodic boundary selection and time alignment of tasks. The task trials are then analyzed spatially using radial basis functions [RBFs] to interpolate demonstrations to span his workspace, using the object position as the motion blending parameter. An analysis of the motions in the object coordinate space [with the origin defined at the object] and absolute world-coordinate space [with the origin defined at the base of the robot], and motion variances in both coordinate frames, leads to a measure [referred to here as objectivity] of how much any part of an action is absolutely oriented, and how much is object-based. A secondary RBF solution, using end effector paths in the object coordinate frame, provides precise end-effector positioning relative to the object. The objectivity measure is used to blend between these two solutions, using the initial RBF solution to preserve quality of motion, and the secondary end-effector objective RBF solution to increase the robot's capability to engage objects accurately and robustly.
Degree
thesis:*- Department dc:contributor.department
- Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2004
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Lieberman, Jeff I. (Jeff Ian), 1978-
- Advisor dc:contributor.advisor
-
- Cynthia Breazeal and J.J. Slotine.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
- Licence dc:rights.uri
- Language dc:language.iso
- en_US
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/27072
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/27072