Geometrically Constrained Trajectory Optimization for Multicopters

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