2026-09-19T16:34:27Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1089822022-01-13T07:54:01Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Russ Tedrake.
Florence, Peter R. (Peter Raymond)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2017-05-11T19:59:03Z
2017-05-11T19:59:03Z
2017
2017
http://hdl.handle.net/1721.1/108982
986497522
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 101-110).
We present a method for robust high-speed quadrotor flight through unknown cluttered environments using integrated perception and control. Motivated by experiments in which the difficulty of accurate state estimation was a primary limitation on speed, our method forgoes maintaining a map in favor of using only instantaneous depth information in the local frame. This provides robustness in the presence of significant state estimate uncertainty. We compare the method against a benchmark approach using a simulated quadrotor race through a forest at high speeds in the presence of increasing state estimate noise. We then present hardware validation experiments in both indoor and outdoor environments, performing robust obstacle avoidance at speeds of up to 10 m/s, including sustained flight through a forest at 6 m/s. Finally, we add to the memoryless method, and develop a robust obstacle avoidance approach that uses memory without resorting to a maximum-likelihood mapping framework.
by Peter R. Florence.
S.M.
110 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Integrated perception and control at high speed
Thesis
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Publication
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<Abstract>We present a method for robust high-speed quadrotor flight through unknown cluttered environments using integrated perception and control. Motivated by experiments in which the difficulty of accurate state estimation was a primary limitation on speed, our method forgoes maintaining a map in favor of using only instantaneous depth information in the local frame. This provides robustness in the presence of significant state estimate uncertainty. We compare the method against a benchmark approach using a simulated quadrotor race through a forest at high speeds in the presence of increasing state estimate noise. We then present hardware validation experiments in both indoor and outdoor environments, performing robust obstacle avoidance at speeds of up to 10 m/s, including sustained flight through a forest at 6 m/s. Finally, we add to the memoryless method, and develop a robust obstacle avoidance approach that uses memory without resorting to a maximum-likelihood mapping framework.</Abstract>
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