Ant colony optimization for agile motion planning
Name
74278842-MIT.pdf
Description
Full printable version
Size
1.88 MB
Format
Adobe PDF
Checksum (MD5)
bac59115fc5eb2267e93571ffd8eb2f0
Author(s)
Krenzke, Tom (Tom Paul)
Advisor(s)
Marc McConley and Brent Appleby.
Date Issued
2006
Publisher
Massachusetts Institute of Technology
Abstract
With the need for greater autonomy in unmanned vehicles growing, design of algorithms for mission-level planning becomes essential. The general field of motion planning for unmanned vehicles falls into this category. Of particular interest is the case of operating in hostile environments with unknown threat locations. When a threat appears, a replan must be quickly formulated and executed. The use of terrain masking to hide from the threat is a vital tactic, which a good algorithm should exploit. In addition, the algorithm should be able to accommodate large search spaces and non-linear objective functions. This thesis investigates the suitability of the Ant Colony Optimization (ACO) heuristic for the agile vehicle motion planning problem. An ACO implementation tailored to the motion planning problem was designed and tested against an existing genetic algorithm solution method for validation. Results show that ACO is indeed a viable option for real-time trajectory generation. ACO' ability to incorporate heuristic information, and its method of solution construction, make it better suited to motion planning problems than existing methods.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.
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. 67-69).
Subjects
Aeronautics and Astronautics.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
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.
Persistent DSpace Link
