The work of this thesis is part of the RoboDeb project, aimed at investigating the application of industrial robots on deburring sheet metal parts. This thesis presents investigations, developments, and implementations of trajectory planning algorithms to automate trajectory design. This thesis first develops custom CAD/CAM software called the Planar Computer Automated Trajectory (PCAT) planning algorithm to establish baseline performance. Trajectory planning is next automated using the novel Planar Image-Space Trajectory (PIST) planning algorithm, which uses computer vision alone to generate machining trajectories. The PIST algorithm is completely automated, with no required CAD data of the workpiece, adapting to new workpieces or manufacturing imperfections. The feasibility of the PIST algorithm is investigated through robotic deburring experimentation, where it successfully deburred the sheet metal parts. The PIST algorithm proved to be the preferred candidate over the PCAT algorithm, as it provided an indistinguishable resulting surface finish while reducing the setup time.