Multi-Stage Parameter Search for Robot Path Planning in Bottom-Up Vat 3D Printing

This article presents an approach to extend the capabilities of vat photopolymerization (VPP) 3D printing using a robotic arm, with a focus on robust path planning. The robotic cell consists of a Mecademic Meca500 six-axis robot mounted on a Zaber X-LRQ300AP linear guide. The kinematic chain is inverted to reflect the logic of VPP: the world reference frame is fixed to the robot’s tool (the build plate), while the tool frame is attached to the polymerization zone. A virtual degree of freedom for screen image rotation is introduced, bringing the system to eight degrees of freedom. Inverse kinematics are solved under constraints (pose tolerance, joint limits, collision avoidance, and continuity) and evaluated using multi-criteria metrics: manipulability, normalized joint-limit margin, and positional/angular sensitivity. The algorithm follows a deterministic coarse-to-fine search procedure: discrete sweeping of global part orientations, initial sampling with Halton sequences, abd feasibility filtering on a sparsified trajectory, followed by refinement and multi-criteria ranking. The pipeline successfully discarded infeasible orientations and identified feasible printing trajectories for six of the seven benchmark parts, while the remaining case highlights a limitation that may be addressed in future improvements.