2026-09-19T00:43:08Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/332942026-06-06T01:04:24Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
John J. Leonard.
Leedekerken, Jacques Chadwick
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-07-13T15:13:10Z
2006-07-13T15:13:10Z
2005
2005
http://hdl.handle.net/1721.1/33294
62278622
Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
Includes bibliographical references (leaves 59-60).
A substantial challenge in robotics is integration of complex software systems for real- time performance. This thesis integrates the robust and generic mapping framework Atlas, a feature-based local Simultaneous Localization and Mapping (SLAM) module, and obstacle avoidance using information from mapped features. The resulting system performs autonomous feature-relative Real-time Obstacle Avoidance and Mapping (ROAM) with laser or sonar range sensors, and results are shown for wide-beam sonar. This system will allow high-speed feature-relative obstacle and avoidance and navigation on mobile robots with wide-beam sonar and/or laser sensors.
by Jacques Chadwick Leedekerken.
M.Eng.
S.B.
60 leaves
2143171 bytes
2144817 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Feature-relative real-time obstacle avoidance and mapping
Thesis
application/pdf
Publication
unknown
unknown
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