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Geometrically Constrained Trajectory Optimization for Multicopters by Wang, Zhepei; Zhou, Xin; Xu, Chao; Gao, Fei is a scholarly article available to read on EtoBox.

What is Geometrically Constrained Trajectory Optimization for Multicopters about?

We present an optimization-based framework for multicopter trajectory planning subject to geometrical configuration constraints and user-defined dynamic constraints. The basis of the framework is a novel trajectory representation built upon our novel optimality conditions for unconstrained control effort minimization. We design linear-complexity operations on this representation to conduct spatial-temporal deformation under various planning requirements. Smooth maps are utilized to exactly eliminate geometrical constraints in a lightweight fashion. A variety of state-input constraints are supported by the decoupling of dense constraint evaluation from sparse parameterization, and backward differentiation of flatness map. As a result, this framework transforms a generally constrained multicopter planning problem into an unconstrained optimization that can be solved reliably and efficiently. Our framework bridges the gaps among solution quality, planning efficiency, and constraint fidelity for a multicopter with limited resources and maneuvering capability. Its generality and robustness are both demonstrated by applications to different flight tasks. Extensive simulations and benchma

Author

Wang, Zhepei; Zhou, Xin; Xu, Chao; Gao, Fei

Published

2021

Language

EN