Autonomous Guidance for the Recovery and Landing of a Remotely Piloted Vehicle

Abstract This paper presents a trajectory optimization algorithm that is applicable to real-time autonomous guidance for the landing of a remotely piloted vehicle. Admissible paths are quickly generated by a two-stage optimisation, where constraint satisfaction takes precedence over optimality. Asymptotic convergence is achieved by restricting the class of constraint functions, and selecting a path parameterisation, such that the cost function is positive definite in the parameter errors. Parameter estimates are initialized by solving a relaxed problem, and subsequent estimates are restricted to a subspace that enforces the boundary conditions A simple numerical example is given to illustrate this approach.