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Autonomous Flight in Unknown Indoor Environments
Author(s) -
Abraham Bachrach,
Ruijie He,
Nicholas Roy
Publication year - 2009
Publication title -
international journal of micro air vehicles
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 21
eISSN - 1756-8307
pISSN - 1756-8293
DOI - 10.1260/175682909790291492
Subject(s) - robot , key (lock) , computer science , drone , extended kalman filter , planner , hierarchy , artificial intelligence , matching (statistics) , simultaneous localization and mapping , sensor fusion , robotics , real time computing , control engineering , mobile robot , engineering , kalman filter , computer security , statistics , genetics , mathematics , economics , market economy , biology
This paper presents our solution for enabling a quadrotor helicopter, equipped with a laser rangefinder sensor, to autonomously explore and map unstructured and unknown indoor environments. While these capabilities are already commodities on ground vehicles, air vehicles seeking the same performance face unique challenges. In this paper, we describe the difficulties in achieving fully autonomous helicopter flight, highlighting the differences between ground and helicopter robots that make it difficult to use algorithms that have been developed for ground robots. We then provide an overview of our solution to the key problems, including a multilevel sensing and control hierarchy, a high-speed laser scan-matching algorithm, an EKF for data fusion, a high-level SLAM implementation, and an exploration planner. Finally, we show experimental results demonstrating the helicopter's ability to navigate accurately and autonomously in unknown environments.Thesis with the same title and author is in DSpace. This is a conference paper.Micro Autonomous Consortium Systems and TechnologySingapore. Armed ForcesNational Science Foundation (U.S.). Division of Information and Intelligent Systems (grant #0546467

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