A perception-guided approach to motion and manipulation planning
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1721.1/52773 |
| _version_ | 1826195089157783552 |
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| author | Wei, Yuan |
| author2 | Nicholas Roy. |
| author_facet | Nicholas Roy. Wei, Yuan |
| author_sort | Wei, Yuan |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. |
| first_indexed | 2024-09-23T10:06:50Z |
| format | Thesis |
| id | mit-1721.1/52773 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:06:50Z |
| publishDate | 2010 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/527732019-04-11T02:05:57Z A perception-guided approach to motion and manipulation planning Perception-guided approach to sampling-based motion and manipulation planning under uncertainty Wei, Yuan Nicholas Roy. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Includes bibliographical references (p. 57-59). Rapidly-Exploring Random Trees (RRT) have been successfully applied to many different robotics systems for motion and manipulation planning under non-holonomic constraints. However, the conventional RRT algorithm may perform poorly in the presence of noise and uncertainty. This thesis proposes a modified form of the algorithm that seeks to reduce the robot's uncertainty in its estimate of the target by choosing solutions that maximize the opportunities for the robot's sensors to perceive the target. This new perception-guided technique will be tested in simulation and compared to the conventional RRT as well as other approaches taken from the literature. The ultimate goal is to integrate this method with a semi-autonomous robotic forklift charged with the task of approaching and picking up a loaded wooden pallet over rough terrain. by Yuan Wei. M.Eng. 2010-03-24T20:36:11Z 2010-03-24T20:36:11Z 2009 2009 Thesis http://hdl.handle.net/1721.1/52773 518077550 eng 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 59 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Wei, Yuan A perception-guided approach to motion and manipulation planning |
| title | A perception-guided approach to motion and manipulation planning |
| title_full | A perception-guided approach to motion and manipulation planning |
| title_fullStr | A perception-guided approach to motion and manipulation planning |
| title_full_unstemmed | A perception-guided approach to motion and manipulation planning |
| title_short | A perception-guided approach to motion and manipulation planning |
| title_sort | perception guided approach to motion and manipulation planning |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/52773 |
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