Localization and tracking of parameterized objects in point clouds

This thesis focuses on object recognition and tracking from three dimensional point cloud renderings of dense range and bearing data. Sensors like laser range-finders and depth cameras have become increasingly popular in autonomous robotic applications. A common task is to locate and track specific objects of interest located somewhere in the point cloud. This often introduces a tedious network of heuristics to build objects from identified primitives or an intractable high dimensional search space. Through a parameterized object model and certain relaxation functions, a likelihood based view of the data can be used to accomplish these goals with increased performance and reliability. Improvements in mathematics and convergence properties have shown that this method can be realized in real time.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Mechanical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2011

Author dc:creator

• Truax, Robert D. (Robert Denison)

Advisor dc:contributor.advisor

• John J. Leonard.

• Mechanical Engineering.

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

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/67805

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/67805