Aircraft three-dimensional hardconstrained trajectory planning using pseudospectral optimization method

Abstract

This paper is concerned with the three-dimensional constrained optimal path planning. To this end, an objective function is defined as the shortest trajectory length in such a way that some constraints including rough terrain avoidance, forbidden zone avoidance, initial and terminal constraints, allowable altitude constraint and maximum allowable curvature of trajectory are satisfied. These leads to a challenging problem for aircraft guidance and control that solution requires great experience, skill, accuracy, and a powerful strategy. For this purpose, pseudospectral technique, which is one of the direct methods, is applied in this paper based on the Chebyshev nodes through which the complexity of the problem is reduced by transforming the optimal control problem into the parametric optimization one. The efficacy of the proposed method is demonstrated by extensive simulations, and it is particularly verified that this method is able to produce a solution satisfying all hard constraints of the underlying problem.

Soft Landing Parameter Measurements for Candidate Navigation Trajectories Using Deep Learning and AI-Enabled Planetary Descent

“…Few researchers solved quadcopter dynamics in 3-dimensional state space for hazard avoidance in a cluttered environment, while few used non-linear dynamics for multi-robot trajectory generation and planning. 3-dimensional trajectory planning for terrain hazard avoidance and optimal control of a spacecraft is demonstrated in work [20].…”