This MSc. thesis explores the design and implementation of a motion planner for non-holonomic autonomous vehicles in parking spaces. The planner must avoid collisions with static obstacles, satisfy performance, comfort and safety constraints for the motion, satisfy the non-holonomic constraints of the vehicle model, consider the dynamics of the vehicle actuators and be fast enough for real-time implementation.

The motion is planned by solving an Optimal Control Problem (OCP) that is discretized in time in order to obtain a non-linear, non-convex, multi-variable optimization problem. The thesis addresses how to solve this optimization problem so that it results in motions that satisfy the requirements. Specifically, the motion is split into a number of waypoint tracking sections, planned by correspondingly simplified optimization problems. The thesis also addresses methods to further simplify the optimization process in order to reduce the implementation time.

The results show the planner satisfies the constraints but does not quite work in real time. Recommendations for improving the planner in the future are given in the report.