The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight
Open accessAbstract
In this letter, we propose a robust and efficient quadrotor motion planning system for fast flight in three-dimensional complex environments. We adopt a kinodynamic path searching method to find a safe, kinodynamic feasible, and minimum-time initial trajectory in the discretized control space. We improve the smoothness and clearance of the trajectory by a B-spline optimization, which incorporates gradient information from a Euclidean distance field and dynamic constraints efficiently utilizing the convex hull property of B-spline. Finally, by representing the final trajectory as a non-uniform B-spline, an iterative time adjustment method is adopted to guarantee dynamically feasible and non-conservative trajectories. We validate our proposed method in various complex simulational environments. The competence of the method is also validated in challenging real-world tasks. We release our code as an open-source package.
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Cites
LOAM: Lidar Odometry and Mapping in Real-time
Zhang, J., & Singh, S. (2014) · Robotics: Science and Systems X · doi:10.15607/rss.2014.x.007 · Cited by 3,303
Minimum snap trajectory generation and control for quadrotors
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Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments
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STOMP: Stochastic trajectory optimization for motion planning
Kalakrishnan, M., Chitta, S., Theodorou, E., Pastor, P., & Schaal, S. (2011) · 2011 IEEE International Conference on Robotics and Automation · doi:10.1109/icra.2011.5980280 · Cited by 876
Elastic bands: connecting path planning and control
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CHOMP: Covariant Hamiltonian optimization for motion planning
Zucker, M., Ratliff, N., Dragan, A. D., Pivtoraiko, M., Klingensmith, M., Dellin, C. M., Bagnell, J. A., & Srinivasa, S. S. (2013) · The International Journal of Robotics Research · doi:10.1177/0278364913488805 · Cited by 758
Polynomial Trajectory Planning for Aggressive Quadrotor Flight in Dense Indoor Environments
Richter, C., Bry, A., & Roy, N. (2016) · Springer Tracts in Advanced Robotics · doi:10.1007/978-3-319-28872-7_37 · Cited by 747
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A Computationally Efficient Motion Primitive for Quadrocopter Trajectory Generation
Mueller, M. W., Hehn, M., & D'Andrea, R. (2015) · IEEE Transactions on Robotics · doi:10.1109/tro.2015.2479878 · Cited by 377
Continuous-time trajectory optimization for online UAV replanning
Oleynikova, H., Burri, M., Taylor, Z., Nieto, J., Siegwart, R., & Galceran, E. (2016) · 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2016.7759784 · Cited by 273
Cited by
Kulathunga, G., Hamed, H., Devitt, D., & Klimchik, A. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3151157 · Cited by 19
Metadata
- Authors
- Zhou, B., Gao, F., Wang, L., Liu, C., & Shen, S.
- Venue
- IEEE Robotics and Automation Letters
- Published
- 2019-10
- Volume
- 4
- Issue
- 4
- Pages
- 3529-3536
- ISSN
- 2377-3766 (ISSN-L)
- 2377-3774
- OpenAlex
- W2962787639
- Cited by
- 747
- References
- 17
- FWCI
- 20.56
- Type
- journal article
- Language
- en
- Open access
- green
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