Multiresolution-based direct trajectory optimization

In this paper we present a multiresolution-based approach for direct trajectory optimization. We transcribe the optimal control problem into a nonlinear programming (NLP) problem and solve the resulting NLP problem on an adaptive grid. The proposed algorithm automatically generates a grid to accurately capture the discontinuities and switchings in the state and control variables. The path constraints are handled with ease using the proposed technique without any additional computational complexity. The efficiency and accuracy of the proposed algorithm is demonstrated with the help of several examples.