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Abstract

Additive manufacturing (3D printing) has evolved from a prototyping tool into a mainstream production technology capable of creating complex, customized parts. However, printing freeform or overhanging geometries without support structures remains a major challenge. Support generation increases material use, post-processing effort, and limits the design freedom that defines the promise of 3D printing. Conventional serial robots and gantry printers are constrained by cumulative joint errors, limited orientation range, and discontinuous trajectories. Parallel robotic systems offer greater stiffness and positional accuracy by distributing loads among multiple actuators, yet they suffer from restricted rotational workspace and complex singularity behaviour. Addressing these limitations is essential for enabling multi-axis, support-free manufacturing. This research develops and integrates the hardware and software foundations for robotic 3D printing using two complementary platforms: a novel kinematically redundant (6+3)-DOF gantry-type robot developed for modeling and trajectory planning, and a kinematically redundant (6+3)-DOF Gosselin-style parallel robot used for simulation and framework validation. A unified framework was implemented that includes (i) inverse-kinematic and Jacobian-based formulations for both robots, (ii) a cubic-polynomial trajectory planner with a Jacobian-aware cost function to ensure smooth, feasible motion, and (iii) a Python-based slicer that converts digital models into joint-space trajectories. Simulation studies verified the continuity, constraint satisfaction, and feasibility of the generated paths for both planar and non-planar geometries. Hardware implementation validated extrusion control and pilot printing using a DYZE system with PID-regulated thermal stability. While synchronized, multi-axis support-free printing remains future work, the integrated results confirm the functional readiness of the trajectory-planning and control framework. The principal contribution of this thesis lies in demonstrating how redundancy-aware trajectory planning and custom slicing can bridge the gap between conventional 3D printing and fully support-free, non-planar fabrication. The developed models, software, and verified hardware platform provide a reproducible foundation for future studies in robotic additive manufacturing, trajectory optimization, and precision multi-axis material deposition.