2020
DOI: 10.1109/tro.2020.2993215
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Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments

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Cited by 123 publications
(90 citation statements)
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References 39 publications
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“…Multirotor flights in tunnel-like confined areas: Multirotor flights in constrained and cluttered environments have been studied for years, and a large amount of motion planning frameworks, together with system integration, have been proposed [12]- [15]. However, flights in tunnel-like confined areas are not as comprehensively studied.…”
Section: Related Workmentioning
confidence: 99%
“…Multirotor flights in tunnel-like confined areas: Multirotor flights in constrained and cluttered environments have been studied for years, and a large amount of motion planning frameworks, together with system integration, have been proposed [12]- [15]. However, flights in tunnel-like confined areas are not as comprehensively studied.…”
Section: Related Workmentioning
confidence: 99%
“…Our article demonstrates the scalability of our method, which can solve problems in corridors with up to more than 40 polyhedra. Gao et al [15] compute safe and aggressive trajectories in real time from human-piloted trajectories, and generates them by alternatively optimizing the spatial and temporal trajectories. However, the two parts optimize different objective functions, so convergence is not guaranteed.…”
Section: A Trajectory Optimization For Uavsmentioning
confidence: 99%
“…To avoid high nonlinearity related to joint space-time optimization, some recent works propose methods that iteratively optimize spatial and time variables in two separate subroutines. The authors in [6] introduced a spatial-temporal optimization method which iteratively refines the geometrical coefficients and time-warping functions via QP and second order cone program (SOCP), respectively. In [9], the authors decomposed the trajectory optimization problem as a bi-level optimization problem where the gradient required in the outer loop is analytically obtained from the dual solution of the inner loop QP.…”
Section: A Trajectory Planning For Quadrotorsmentioning
confidence: 99%
“…where denotes the tensor contraction and f is defined in (6). In addition to the decision variable δu k (i.e., the first order variation of u k ), the primal-dual version of DDP introduces the additional decision variable δλ k .…”
Section: The Overall Problem and Algorithmmentioning
confidence: 99%
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