  In this paper, we develop a computationally-efficient approach to
minimum-time trajectory optimization using input-output data-based models, to
produce an end-to-end data-to-control solution to time-optimal planning/control
of dynamic systems and hence facilitate their autonomous operation. The
approach integrates a non-parametric data-based model for trajectory prediction
and a continuous optimization formulation based on an exponential weighting
scheme for minimum-time trajectory planning. The optimization problem in its
final form is a linear program and is easy to solve. We validate the approach
and illustrate its application with a spacecraft relative motion planning
problem.
