Abstract
In this paper, we propose an effective and hierarchical planning framework for quadrotor fast autonomous flight. In the front-end, we propose an efficient guided sampling strategy by topology graph. In the back-end, the traditional trajectory optimization problems are formulated as minimising an objective function such as total energy cost while considering safety and dynamic feasibility constraints. However, the time characteristic is ignored. In this paper, the time optimal trajectory is studied, the time optimal trajectory problem is transformed to a convex optimization problem with a time optimal guidance trajectory based on the Pontryagin’s Minimum Principle. The simulation experimental results demonstrate the feasibility and validity of the proposed motion planning method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arrizabalaga, J., Ryll, M.: Towards time-optimal tunnel-following for quadrotors. In: 2022 International Conference on Robotics and Automation (ICRA), pp. 4044–4050 (2022). https://doi.org/10.1109/ICRA46639.2022.9811764
Beul, M., Behnke, S.: Analytical time-optimal trajectory generation and control for multirotors. In: 2016 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 87–96. IEEE (2016)
Chen, J., Liu, T., Shen, S.: Online generation of collision-free trajectories for quadrotor flight in unknown cluttered environments. In: 2016 IEEE International Conference on Robotics and Automation (ICRA), pp. 1476–1483. IEEE (2016)
Dijkstra, E.W.: A note on two problems in connexion with graphs. In: Edsger Wybe Dijkstra: His Life, Work, and Legacy, pp. 287–290 (2022)
Gao, F., Wang, L., Zhou, B., Zhou, X., Pan, J., Shen, S.: Teach-repeat-replan: a complete and robust system for aggressive flight in complex environments. IEEE Trans. Rob. 36(5), 1526–1545 (2020)
Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybern. 4(2), 100–107 (1968)
Hehn, M., Ritz, R., D’Andrea, R.: Performance benchmarking of quadrotor systems using time-optimal control. Auton. Robot. 33, 69–88 (2012)
Hsu, D., Kindel, R., Latombe, J.C., Rock, S.: Randomized kinodynamic motion planning with moving obstacles. Int. J. Robot. Res. 21(3), 233–255 (2002)
Karaman, S., Frazzoli, E.: Sampling-based algorithms for optimal motion planning. Int. J. Robot. Res. 30(7), 846–894 (2011)
Kavraki, L.E., Svestka, P., Latombe, J.C., Overmars, M.H.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. Autom. 12(4), 566–580 (1996)
Liu, S., Atanasov, N., Mohta, K., Kumar, V.: Search-based motion planning for quadrotors using linear quadratic minimum time control. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2872–2879. IEEE (2017)
Mellinger, D., Kumar, V.: Minimum snap trajectory generation and control for quadrotors. In: 2011 IEEE International Conference on Robotics and Automation, pp. 2520–2525. IEEE (2011)
Romero, A., Penicka, R., Scaramuzza, D.: Time-optimal online replanning for agile quadrotor flight. IEEE Robot. Autom. Lett. 7(3), 7730–7737 (2022)
Romero, A., Sun, S., Foehn, P., Scaramuzza, D.: Model predictive contouring control for time-optimal quadrotor flight. IEEE Trans. Rob. 38(6), 3340–3356 (2022)
Van Loock, W., Pipeleers, G., Swevers, J.: Time-optimal quadrotor flight. In: 2013 European Control Conference (ECC), pp. 1788–1792. IEEE (2013)
Ye, H., Zhou, X., Wang, Z., Xu, C., Chu, J., Gao, F.: TGK-planner: an efficient topology guided kinodynamic planner for autonomous quadrotors. IEEE Robot. Autom. Lett. 6(2), 494–501 (2020)
Zhang, G., He, Y., Dai, B., Gu, F., Yang, L., Han, J., et al.: Optimal trajectory planning of a quadrotor toward free flying target catching. Inf. Control 48, 469–476 (2019)
Zhang, G., et al.: Guided time-optimal model predictive control of a multi-rotor. IEEE Control Syst. Lett. 7, 1658–1663 (2023). https://doi.org/10.1109/LCSYS.2023.3277319
Zhou, B., Gao, F., Wang, L., Liu, C., Shen, S.: Robust and efficient quadrotor trajectory generation for fast autonomous flight. IEEE Robot. Autom. Lett. 4(4), 3529–3536 (2019)
Zucker, M., et al.: Chomp: covariant hamiltonian optimization for motion planning. Int. J. Robot. Res. 32(9–10), 1164–1193 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Nie, H., Chen, J., Zhang, G., Li, D., He, Y. (2023). Efficient and Hierarchical Quadrotor Planner for Fast Autonomous Flight. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14274. Springer, Singapore. https://doi.org/10.1007/978-981-99-6501-4_15
Download citation
DOI: https://doi.org/10.1007/978-981-99-6501-4_15
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-6500-7
Online ISBN: 978-981-99-6501-4
eBook Packages: Computer ScienceComputer Science (R0)