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Selected papers from the 2nd International Symposium on UAVs, Reno, Nevada, U.S.A. June 8–10, 2009 pp 101–122Cite as

An Efficient Path Planning and Control Algorithm for RUAV’s in Unknown and Cluttered Environments

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Abstract

This paper presents an efficient planning and execution algorithm for the navigation of an autonomous rotary wing UAV (RUAV) manoeuvering in an unknown and cluttered environment. A Rapidly-exploring Random Tree (RRT) variant is used for the generation of a collision free path and linear Model Predictive Control(MPC) is applied to follow this path. The guidance errors are mapped to the states of the linear MPC structure by using the nonlinear kinematic equations. The proposed path planning algorithm considers the run time of the planning stage explicitly and generates a continuous curvature path whenever replanning occurs. Simulation results show that the RUAV with the proposed methodology successfully achieves autonomous navigation regardless of its lack of prior information about the environment.

This work is supported in part by the ARC Centre of Excellence programme, funded by the Australian Research Council (ARC) and the New South Wales State Government.

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Authors and Affiliations

  1. Australian Centre for Field Robotics, University of Sydney, Sydney, New South Wales, 2006, Australia

    Kwangjin Yang, Seng Keat Gan & Salah Sukkarieh

Authors
  1. Kwangjin Yang
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  2. Seng Keat Gan
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  3. Salah Sukkarieh
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Corresponding author

Correspondence to Kwangjin Yang .

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, CMK 300 School of Engineering and Computer Science, University of Denver, Denver, CO, 80208, USA

    Kimon P. Valavanis

  2. Dept. Electrical & Computer Engineering, Brigham Young University, Provo, UT, 84602, USA

    Randal Beard

  3. Applied Engineering Technology Program, Drexel University, 3001 One Drexel Plaza, Market St., Philadelphia, PA, 19104, USA

    Paul Oh

  4. Depto. Ingeniera Sistemas y Automática Camino de los Descubrimientos, Universidad de Sevilla Escuela Superior de Ingenieros, s/n 41092, Sevilla, Spain

    Aníbal Ollero

  5. Dept. Computer Science & Engineering, University of South Florida, 4202 E. Fowler Ave., Tampa, FL, 33620, USA

    Leslie A. Piegl

  6. Korea Advanced Institute of Science & Technology (KAIST), Department of Aerospace Engineering, 373-1 Guseong-dong Daejeon 305-701 Yuseong-gu, Republic of South Korea

    Hyunchui Shim

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© 2009 Springer Science + Business Media B.V.

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Yang, K., Gan, S.K., Sukkarieh, S. (2009). An Efficient Path Planning and Control Algorithm for RUAV’s in Unknown and Cluttered Environments. In: Valavanis, K.P., Beard, R., Oh, P., Ollero, A., Piegl, L.A., Shim, H. (eds) Selected papers from the 2nd International Symposium on UAVs, Reno, Nevada, U.S.A. June 8–10, 2009. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8764-5_6

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  • DOI: https://doi.org/10.1007/978-90-481-8764-5_6

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-8763-8

  • Online ISBN: 978-90-481-8764-5

  • eBook Packages: EngineeringEngineering (R0)

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