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A Collaborative Aerial-Ground Robotic System for Fast Exploration

Conference paper
Part of the Springer Proceedings in Advanced Robotics book series (SPAR, volume 11)

Abstract

Exploration of unknown environments using autonomous robots has been considered a fundamental problem in robotics applications such as search and rescue [10], industrial inspection and 3D modelling.

Supplementary material

Supplementary material 1 (mp4 37738 KB)

References

  1. 1.
    Butzkey, J., Dornbushy, A., Likhachevy, M.: 3-D exploration with an air-ground robotic system. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3241–3248 (2015)Google Scholar
  2. 2.
    Cieslewski, T., Kaufmann, E., Scaramuzza, D.: Rapid exploration with multi-rotors: a frontier selection method for high speed flight. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2135–2142 (2017)Google Scholar
  3. 3.
    Connolly, C.: On the application of harmonic functions to robotics. J. Robot. Syst. 10, 931–946 (1993)CrossRefGoogle Scholar
  4. 4.
    Delmerico, J., Mueggler, E., Nitsch, J., Scaramuzza, D.: Active autonomous aerial exploration for ground robot path planning. IEEE Robot. Autom. Lett. 2(2), 664–671 (2017)CrossRefGoogle Scholar
  5. 5.
    Silva, E.P., Engel, P.M., Trevisan, M., Idiart, M.A.P.: Exploration method using harmonic functions. Robot. Auton. Syst. 40(1), 25–42 (2002)CrossRefGoogle Scholar
  6. 6.
    Gao, F., Wu, W., Lin, Y., Shen, S.: Online safe trajectory generation for quadrotors using fast marching method and Bernstein basis polynomial. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (2018)Google Scholar
  7. 7.
    Likhachev, M., Ferguson, D.: Planning long dynamically feasible maneuvers for autonomous vehicles. Int. J. Robot. Res. 28(8), 933–945 (2009)CrossRefGoogle Scholar
  8. 8.
    Mellinger, D., Kumar, V.: Minimum snap trajectory generation and control for quadrotors. In: International Conference on Robotics and Automation (ICRA), pp. 2520–2525. IEEE (2011)Google Scholar
  9. 9.
    Qin, T., Li, P., Shen, S.: VINS-Mono: a robust and versatile monocular visual-inertial state estimator. arXiv preprint arXiv:1708.03852 (2017)
  10. 10.
    Shen, C., Zhang, Y., Li, Z., Gao, F., Shen, S.: Collaborative air-ground target searching in complex environments. In: IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), pp. 230–237 (2017)Google Scholar
  11. 11.
    Verriest, E.I., Lewis, F.L.: On the linear quadratic minimum-time problem. IEEE Trans. Autom. Control 36(7), 859–863 (1991)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Yamauchi, B.: A frontier-based approach for autonomous exploration. In: Proceedings of 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 1997, pp. 146–151 (1997)Google Scholar
  13. 13.
    Zhang, J., Singh, S.: LOAM: lidar odometry and mapping in real-time. In: Robotics: Science and Systems Conference (2014)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.The Hong Kong University of Science and TechnologyKowloonHong Kong
  2. 2.Beihang UniversityBeijingChina

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