Vision-assisted Arm Motion Planning for Freeform 3D Printing

Rapid freeform 3D printing of heated polymeric materials to create 3D curves in aerial space instead of 2D layers is a growing research area. We develop an arm motion planning technique that can increase printing accuracy without loss of the printing speed. The method is based on an actor-critic model-free deep reinforcement learning algorithm that operates over continuous arm action spaces. The proposed technique is able to find the trajectory for the arm that can neutralize the effect of gravity and build a filament with the desired shape. Experimental results are presented to illustrate the effectiveness of this technique in printing a straight line as well as a more difficult semicircle filament in the vertical plane.