2026-09-19T12:44:51Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/899922026-06-16T18:52:26Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Leslie Pack Kaelbling and Tomás Lozano-Pérez.
Glover, Jared Marshall
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-09-19T21:33:06Z
2014-09-19T21:33:06Z
2014
2014
http://hdl.handle.net/1721.1/89992
890131601
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 145-154).
Over the past few years, the field of robotic computer vision has undergone a 3-D revolution. One of the biggest challenges in dealing with 3-D geometry lies in appropriately handling 3-D rotational data. To specify "where" an object is in space, one must provide both a position and an orientation for the object. Noise and ambiguity in the robot's sensory data necessitate a robust model for representing uncertainty on the space of 3-D orientations. This is given by the quaternion Bingham distribution-a maximum entropy probability distribution on the 4-D unit quaternion hypersphere. In this thesis, we apply the quaternion Bingham to two applications: 3-D object instance detection from RGB-D images, and robot ping pong. The Bingham enables our object detection system to achieve state-of-the-art detection rates in highly cluttered scenes, while also enabling the ping pong robot to track the orientation and spin on flying ping pong balls. To enable the robot to actually play ping pong, we also explored a new method for incorporating human advice into a robot's motor control exploration policies.
by Jared Marshall Glover.
Ph.D.
154 pages
eng
Massachusetts Institute of Technology
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.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
The quaternion Bingham Distribution, 3D object detection, and dynamic manipulation
Thesis
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<Abstract>Over the past few years, the field of robotic computer vision has undergone a 3-D revolution. One of the biggest challenges in dealing with 3-D geometry lies in appropriately handling 3-D rotational data. To specify "where" an object is in space, one must provide both a position and an orientation for the object. Noise and ambiguity in the robot's sensory data necessitate a robust model for representing uncertainty on the space of 3-D orientations. This is given by the quaternion Bingham distribution-a maximum entropy probability distribution on the 4-D unit quaternion hypersphere. In this thesis, we apply the quaternion Bingham to two applications: 3-D object instance detection from RGB-D images, and robot ping pong. The Bingham enables our object detection system to achieve state-of-the-art detection rates in highly cluttered scenes, while also enabling the ping pong robot to track the orientation and spin on flying ping pong balls. To enable the robot to actually play ping pong, we also explored a new method for incorporating human advice into a robot's motor control exploration policies.</Abstract>
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