Feature-relative real-time obstacle avoidance and mapping
Author(s)Leedekerken, Jacques Chadwick
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
John J. Leonard.
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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.
Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (leaves 59-60).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.