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JRM Vol.28 No.6 pp. 878-886
doi: 10.20965/jrm.2016.p0878
(2016)

Paper:

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State Estimation and Control of an Unmanned Air Vehicle from a Ground-Based 3D Laser Scanner

Ryan Arya Pratama and Akihisa Ohya

Graduate School of Systems and Information Engineering, University of Tsukuba
1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

Received:
May 26, 2016
Accepted:
September 26, 2016
Published:
December 20, 2016
Creative Commons License
Keywords:
UAV, data fusion, control, 3D laser scanner
Abstract
In this work, we present a system to estimate the state of and control an Unmanned Air Vehicle (UAV) from a ground-based 3D laser scanner. The main contributions of this work are on data fusion between a low-frequency 3D laser scanner with considerable delay and an on-board 6-DOF IMU, and on automatic position control of a UAV using state estimate obtained from the fusion. We measured laser delay using data from a manually controlled flight. We have devised a method to perform online estimation and compensation of accelerometer offset using delay-corrected laser measurement. We then use the UAV state estimation in a nested controller with a high-frequency velocity control inner loop and a low-frequency position control outer loop. We demonstrated the state estimation and control in a series of experiments on velocity control and position control, including a comparison between position control using fusion data and only laser data.
UAV state estimation from laser scanner

UAV state estimation from laser scanner

Cite this article as:
R. Pratama and A. Ohya, “State Estimation and Control of an Unmanned Air Vehicle from a Ground-Based 3D Laser Scanner,” J. Robot. Mechatron., Vol.28 No.6, pp. 878-886, 2016.
Data files:
References
  1. [1] S. Lupashin, A. Schollig, M. Hehn, and R. D’Andrea, “The Flying Machine Arena as of 2010,” 2011 IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 2970-2971, 2011.
  2. [2] N. Michael, D. Mellinger, Q. Lindsey, and V. Kumar, “The grasp multiple micro-uav testbed,” IEEE Robotics & Automation Magazine, Vol.17, No.3, pp. 56-65, 2010.
  3. [3] M. F. B. Abas, D. Pebrianti, S. A. M. Ali, D. Iwakura, Y. Song, K. Nonami, and D. Fujiwara, “Circular Leader-Follower Formation Control of Quad-rotor Aerial Vehicles,” J. of Robotics and Mechatronics, Vol.25, No.1, pp. 60-71, 2013.
  4. [4] K. Sato and R. Daikoku, “A Simple Autonomous Flight Control of Multicopter Using Only Web Camera,” J. of Robotics and Mechatronics, Vol.28, No.3, pp. 286-294, 2016.
  5. [5] J. Engel, J. Sturm, and D. Cremers, “Camera-Based Navigation of a Low-Cost Quadrocopter,” Proc. of the Int. Conf. on Intelligent Robot Systems (IROS), Oct. 2012.
  6. [6] D. Iwakura and K. Nonami, “Indoor localization of flying robot by means of infrared sensors,” J. of Robotics and Mechatronics, Vol.25, No.1, pp. 201-210, 2013.
  7. [7] N. Michael, J. Fink, and V. Kumar, “Controlling a team of ground robots via an aerial robot,” IEEE/RSJ Int. Conf. on Intelligent Robots and Systems 2007 (IROS 2007), pp. 965-970, 2007.
  8. [8] C. Luo, A. P. Espinosa, A. De Gloria, and R. Sgherri, “Air-ground multi-agent robot team coordination,” 2011 IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 6588-6591, 2011.
  9. [9] Y. Cai and S. Kousuke, “Geometric Relation matching based object identification for UAV and UGV cooperation,” 2015 Conf. on Technologies and Applications of Artificial Intelligence (TAAI), pp. 478-483, 2015.
  10. [10] M. Faessler, E. Mueggler, K. Schwabe, and D. Scaramuzza, “A Monocular Pose Estimation System based on Infrared LEDs,” IEEE Int. Conf. on Robotics and Automation (ICRA), Hong Kong, 2014.
  11. [11] J. Mart’inez, A. Pequeno-Boter, A. Mandow, A. Garc’ia-Cerezo, and J. Morales, “Progress in mini-helicopter tracking with a 3D laser range-finder,” World Congress, Vol.16, pp. 1377-1377, 2005.
  12. [12] R. A. Pratama and A. Ohya, “Tracking and control of a small unmanned aerial vehicle using a ground-based 3D laser scanner,” 2014 IEEE/SICE Int. Symposium on System Integration (SII), pp. 718-723, Dec. 2014.
  13. [13] O. Wulf and B. Wagner, “Fast 3D scanning methods for laser measurement systems,” Int. Conf. on control systems and computer science (CSCS14), pp. 2-5, 2003.
  14. [14] J. Morales, J. L. Martinez, A. Mandow, A. Pequeño-Boter, and A. Garcia-Cerezo, “Design and development of a fast and precise low-cost 3D laser rangefinder,” 2011 IEEE Int. Conf. on Mechatronics (ICM), pp. 621-626, 2011.
  15. [15] K. Ohno, S. Tadokoro, K. Nagatani, E. Koyanagi, and T. Yoshida, “3-D mapping of an underground mall using a tracked vehicle with four sub-tracks,” 2009 IEEE Int. Workshop on Safety, Security & Rescue Robotics (SSRR), pp. 1-6, 2009.
  16. [16] M. Quigley, K. Conley, B. P. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, and A. Y. Ng, “ROS: an open-source Robot Operating System,” ICRA Workshop on Open Source Software, 2009.

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