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您的检索式：作者名="Binfeng Pan"
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| 1 | Survey of convex optimization for aerospace applications显示文摘Convex optimization is a class of mathematical programming problems with polynomial complexity for which state-of-the-art, highly efficient numerical algorithms with predeterminable computational bounds exist. Computational efficiency and tractability in aerospace engineering, especially in guidance, navigation, and control (GN&C), are of paramount importance. With theoretical guarantees on solutions and computational efficiency, convex optimization lends itself as a very appealing tool. Coinciding the strong drive toward autonomous operations of aerospace vehicles, convex optimization has seen rapidly increasing utility in solving aerospace GN&C problems with the potential for onboard real-time applications. This paper attempts to provide an overview on the problems to date in aerospace guidance, path planning, and control where convex optimization has been applied. Various convexification techniques are reviewed that have been used to convexify the originally nonconvex aerospace problems. Discussions on how to ensure the validity of the convexification process are provided. Some related implementation issues will be introduced as well. | Xinfu Liu Ping Lu Binfeng Pan | 2017 | Astrodynamics2017，1，1： | 32 |
| 2 | A survey on artificial intelligence trends in spacecraft guidance dynamics and control显示文摘The rapid developments of artificial intelligence in the last decade are influencing aerospace engineering to a great extent and research in this context is proliferating.We share our observations on the recent developments in the area of spacecraft guidance dynamics and control,giving selected examples on success stories that have been motivated by mission designs.Our focus is on evolutionary optimisation,tree searches and machine learning,including deep learning and reinforcement learning as the key technologies and drivers for current and future research in the field.From a high-level perspective,we survey various scenarios for which these approaches have been successfully applied or are under strong scientific investigation.Whenever possible,we highlight the relations and synergies that can be obtained by combining different techniques and projects towards future domains for which newly emerging artificial intelligence techniques are expected to become game changers. | Dario Izzo Marcus Martens Binfeng Pan | 2019 | Astrodynamics2019，3，4： | 15 |
| 3 | Highly constrained optimal launch ascent guidance 显示文摘 | Lu Ping Pan Binfeng | 2010 | Journal of Guidance Control and Dynamics2010，33，2： | 1 |
| 4 | Message from the Guest Editors of the Special Issue on Applications of Artificial Intelligence in Aerospace Engineering显示文摘Dear authors and readers,Artificial intelligence(AI)has recently found many new applications in aerospace engineering,which range from long-term scheduling of space telescope observations to science planning for the Rosetta mission,from AI-based“astronaut assistant”in International Space Station to AI instrument equipped in the Mars rover Curiosity.The current perception is that methods and techniques developed within the AI research field have the potential to revolutionize almost every aspect of space exploration.It is thus very important for aerospace engineers to monitor the advances on the state-of-the-art methods available in the AI field and be aware of their proposed applications,owing to which,this special issue is organized. | Dario Izzo Marcus Martens Binfeng Pan | 2019 | Astrodynamics2019，3，4： | 0 |
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