Numerical methods for time-optimal motion planning applications

Industrial automation tasks in a competitive economic context often map in a natural way to time-optimal control problems for mechatronic systems. These problems are semi-infinite and nonconvex in nature. Some form of gridding is required to solve them with a tractable numerical method. This thesis develops methodologies for gridding more efficiently, especially benefitting systems with rich dynamics and problems with long planning horizons.