The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Minimum snap trajectory generation and control for quadrotors
Abstract
We address the controller design and the trajectory generation for a quadrotor maneuvering in three dimensions in a tightly constrained setting typical of indoor environments. In such settings, it is necessary to allow for significant excursions of the attitude from the hover state and small angle approximations cannot be justified for the roll and pitch. We develop an algorithm that enables the real-time generation of optimal trajectories through a sequence of 3-D positions and yaw angles, while ensuring safe passage through specified corridors and satisfying constraints on velocities, accelerations and inputs. A nonlinear controller ensures the faithful tracking of these trajectories. Experimental results illustrate the application of the method to fast motion (5-10 body lengths/second) in three-dimensional slalom courses.
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Cites
The coordination of arm movements: an experimentally confirmed mathematical model
Flash, T., & Hogan, N. (1985) · The Journal of Neuroscience · doi:10.1523/jneurosci.05-07-01688.1985 · Cited by 4,395
Geometric tracking control of a quadrotor UAV on SE(3)
Lee, T., Leok, M., & McClamroch, N. H. (2010) · 49th IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2010.5717652 · Cited by 1,376
The GRASP Multiple Micro-UAV Testbed
Michael, N., Mellinger, D., Lindsey, Q., & Kumar, V. (2010) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2010.937855 · Cited by 768
Self-citationARA*: Anytime A* with Provable Bounds on Sub-Optimality
Likhachev, M. A., Gordon, G. J., & Thrun, S. (2003) · Cited by 574
A simple learning strategy for high-speed quadrocopter multi-flips
Lupashin, S., Schöllig, A., Sherback, M., & D'Andrea, R. (2010) · 2010 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.2010.5509452 · Cited by 278
Real-time trajectory generation for differentially flat systems
Van Nieuwstadt, M. J., & Murray, R. M. (1998) · International Journal of Robust and Nonlinear Control · doi:10.1002/(sici)1099-1239(199809)8:11<995::aid-rnc373>3.0.co;2-w · Cited by 264
A simple learning strategy for high-speed quadrocopter multi-flips
Lupashin, S., Schoellig, A. P., Sherback, M., & D’Andrea, R. (2009) · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · doi:10.3929/ethz-a-005888743 · Cited by 242
On the stability of receding horizon control with a general terminal cost
Jadbabaie, A., & Hauser, J. (2005) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.846597 · Cited by 204
Nonlinear model predictive tracking control for rotorcraft-based unmanned aerial vehicles
Kim, H. J., Shim, D. H., & Sastry, S. (2002) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2002.1024483 · Cited by 196
LQR-trees: Feedback motion planning on sparse randomized trees
Tedrake, R. (2009) · Robotics: Science and Systems · doi:10.15607/rss.2009.v.003 · Cited by 158
Cited by
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
Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight
Zhou, B., Gao, F., Wang, L., Liu, C., & Shen, S. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2927938 · Cited by 747
Swarm of micro flying robots in the wild
Zhou, X., Wen, X., Wang, Z., Gao, Y., Li, H., Wang, Q., Yang, T., Lu, H., Cao, Y., Xu, C., et al. (2022) · Science Robotics · doi:10.1126/scirobotics.abm5954 · Cited by 657
Liu, S., Watterson, M., Mohta, K., Sun, K., Bhattacharya, S., Taylor, C. J., & Kumar, V. (2017) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2017.2663526 · Cited by 555
Self-citationCamera-based navigation of a low-cost quadrocopter
Engel, J., Sturm, J., & Cremers, D. (2012) · 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems · doi:10.1109/iros.2012.6385458 · Cited by 349
Metadata
- Authors
- Mellinger, D., & Kumar, V.
- Venue
- 2011 IEEE International Conference on Robotics and Automation
- Publisher
- IEEE
- Published
- 2011-05
- Pages
- 2520-2525
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W2162991084
- Cited by
- 2,367
- References
- 13
- FWCI
- 37.55
- Type
- conference paper
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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