Abstract
This paper describes a novel algorithm for generating flight paths in real time that avoid turbulent regions detected by an onboard Doppler lidar. Adopting the distance traveled rather than the time as the independent variable in the state equations enables an exact expression to be obtained for the point-mass dynamics and reduces the number of constraints imposed by turbulence avoidance. Moreover, the algorithm estimates the global optimum by applying second-order cone programming relaxation to the original nonconvex problem. Based on this estimate, it then applies convex quadratic programming. This algorithm is well suited for real-time applications since it is guaranteed to converge in polynomial computation time and it is expected to generate practically useful paths. The high computational speed of the algorithm is demonstrated and the physical feasibilities of the calculated paths are analyzed by numerically simulating turbulence avoidance.
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