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A robust online path planning approach in cluttered environments for micro rotorcraft drones

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Abstract

We present in this paper a robust online path planning method, which allows a micro rotorcraft drone to fly safely in GPS-denied and obstacle-strewn environments with limited onboard computational power. The approach is based on an efficiently managed grid map and a closed-form solution to the two point boundary value problem (TPBVP). The grid map assists trajectory evaluation whereas the solution to the TPBVP generates smooth trajectories. Finally, a top-level trajectory switching algorithm is utilized to minimize the computational cost. Advantages of the proposed approach include its conservation of computational resource, robustness of trajectory generation and agility of reaction to unknown environment. The result has been realized on actual drones platforms and successfully demonstrated in real flight tests. The video of flight tests can be found at: http://uav.ece.nus.edu.sg/robust-online-path-planning-Lai2015.html.

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Authors and Affiliations

  1. NUS Graduate School for Integrative Sciences & Engineering, National University of Singapore, Singapore, 117456, Singapore

    Shupeng Lai

  2. Department of Electrical & Computer Engineering, National University of Singapore, Singapore, 117583, Singapore

    Kangli Wang & Ben M. Chen

  3. Temasek Laboratories, National University of Singapore, Singapore, 117411, Singapore

    Hailong Qin & Jin Q. Cui

Authors
  1. Shupeng Lai
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  2. Kangli Wang
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  3. Hailong Qin
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  4. Jin Q. Cui
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  5. Ben M. Chen
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Corresponding author

Correspondence to Shupeng Lai.

Additional information

Shupeng LAI received his B.Eng. degree from the Department of Electronic and Electrical Engineering, Nanyang Technological University in 2012. He is currently a Ph.D. candidate at National University of Singapore. His research interests lie in game theory and navigation of multiple unmanned systems.

Kangli WANG received his B.Eng. degree from the Department of Electrical and Computer Engineering (ECE) at National University of Singapore (NUS) in 2013. He has joined NUS UAV team since 2012 during his undergraduate studies. He is currently pursuing his Ph.D. degree in ECE at the NUS under presidential graduate fellowship scholarship. His main research area is design and development of unconventional UAV with vertical takeoff and landing and cruise fly ability. He is also interested in flight control system design.

Hailong QIN received his B.Eng. degree in Mechatronics from Harbin Institute of Technology, Harbin China, in 2011, and M.Eng. degree in Mechanical Engineering from Pohang University of Technology, Pohang Korea, in 2013. He is currently a research engineer and part-time Ph.D. candidate at National University of Singapore. His research interests includes 3D reconstruction and visual navigation.

Jinqiang CUI received his B.Sc. and M.Sc. degrees in Mechatronic Engineering from Northwestern Polytechnical University, Xi’an, China, in 2005 and 2008, respectively. He received his Ph.D. in Electrical and Computer Engineering from National University of Singapore (NUS) in 2015. In the Ph.D. study, his research interest is navigation of unmanned aerial vehicles (UAV) in GPS-denied environments, especially forest. Currently, he is a research scientist in the Control Science Group at NUS Temasek Laboratories. His research interests are GPS-less navigation using LIDAR and vision sensing technologies.

Ben M. CHEN is currently a Professor and Director of Control, Intelligent Systems & Robotics Area, Department of Electrical and Computer Engineering, National University of Singapore (NUS), and Head of Control Science Group, NUS Temasek Laboratories. His current research interests are in systems and control, unmanned aerial systems, and financial market modeling. Dr. Chen is an IEEE Fellow. He is the author/co-author of 10 research monographs includingH2 Optimal Control (Prentice Hall, 1995), Robust andHControl (Springer, 2000), Hard Disk Drive Servo Systems (Springer, 1st Edition, 2002; 2nd Edition, 2006), Linear Systems Theory (Birkh¨auser, 2004), Unmanned Rotorcraft Systems (Springer, 2011), and Stock Market Modeling and Forecasting (Springer, 2013). He had served on the editorial boards of a number of journals including IEEE Transactions on Automatic Control, Systems & Control Letters, and Automatica. He currently serves as an Editor-in-Chief of Unmanned Systems and a Deputy Editor-in-Chief of Control Theory & Technology.

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Lai, S., Wang, K., Qin, H. et al. A robust online path planning approach in cluttered environments for micro rotorcraft drones. Control Theory Technol. 14, 83–96 (2016). https://doi.org/10.1007/s11768-016-6007-8

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  • DOI: https://doi.org/10.1007/s11768-016-6007-8

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