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- W4362502005 abstract "Visual pose estimation is essential for many space applications, such as autonomous robots for planetary exploration, asteroid exploration, and spacecraft pose estimation. However, the high reliability requirement of space applications cannot be satisfied by general visual pose estimation algorithms based on heuristic local optimization. This paper briefly introduce certifiable optimal algorithms for the visual pose estimation framework to the aerospace research community, including both visual relative pose estimation problem and pose-graph optimization problem. The original optimization problem is reformulated as a quadratically constrained quadratic program (QCQP) problem, whose Lagrangian dual function is a semidefinite programming (SDP) problem which is convex. Simulation results demonstrate the feasibility of certifiable optimal visual pose estimation algorithms based on the zero duality gap for typical application scenarios." @default.
- W4362502005 created "2023-04-05" @default.
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- W4362502005 date "2023-01-01" @default.
- W4362502005 modified "2023-09-26" @default.
- W4362502005 title "Certifiable Optimal Visual Pose Estimation for Space Applications" @default.
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- W4362502005 doi "https://doi.org/10.1007/978-981-99-1256-8_28" @default.
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