Trajectory Optimization Under Uncertainty is a trajectory optimization framework that incorporates probabilistic or bounded uncertainty in system dynamics, disturbances, or measurements, distinguishing itself by explicitly ensuring constraint satisfaction and performance robustness under uncertain conditions.
125
Publications
4.2K
Citations
354
Authors
148
Institutions
Publications per year
2017–2026
69
Parents
Publications
125
1–5 of 125
Authors
354
- CG
5
h-index
- SC
3
h-index
- AT
3
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- RC
3
h-index
- JL
2
h-index
1–5 of 354
Institutions
148
Massachusetts Institute of Technology
Cambridge, United States
7 h-index
18 publications
992 citations
Beijing Institute of Technology
Beijing, China
7 h-index
18 publications
659 citations
ETH Zurich
Zurich, Switzerland
5 h-index
13 publications
484 citations
Boston University
Boston, United States
5 h-index
11 publications
439 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
8 publications
180 citations
University of Michigan
Ann Arbor, United States
3 h-index
4 publications
60 citations
Max Planck Institute for Intelligent Systems
Stuttgart, Germany
3 h-index
7 publications
117 citations
University of Toronto
Toronto, Canada
3 h-index
9 publications
555 citations
1–8 of 148
Venues
- Journal of Guidance Control and Dynamics
17 publications · 621 citations
17
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- IEEE Transactions on Automatic Control
6 publications · 322 citations
6
h-index
- Acta Astronautica
5 publications · 137 citations
5
h-index
- Transportation Research Part C Emerging Technologies
4 publications · 177 citations
4
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- Aerospace Science and Technology
AST · 3 publications · 123 citations
3
h-index
1–5