Automation by means of robotics for additive manufacturing (AM) technologies offers greater freedom of movement compared with conventional gantry designs, larger print volumes by virtue of mobility around the printing space on wheels or rails, and reduced human supervision and interaction. This project is focused on enabling robotic manipulators with 3D printing capabilities to advance the area of robotic-driven AM. The work is focused on designing specialized end-effector systems for 3D printing applications, creating robust and coordinated control structures for creating high accuracy samples, and leveraging machine learning techniques to reduce the trial-and error campaigns for tuning the parameters of 3D printing.
Luis Velazquez, MS Student in Mechanical Engineering, email: firstname.lastname@example.org
Jennifer M Hoang-Nguyen, Undergraduate Student in Mechanical Engineering, email: email@example.com
 L. Weger, L. Velazquez, C. Barbalata, D. Roy, and G. Palardy, “Curing behavior simulator for robotic 3D printing of UV-curable thermoset polymers,” in Society of Plastics Engineering, Annual Technical Conference (SPE ANTEC), 2022.
 L. Velazquez, G. Palardy, and C. Barbalata, “Design and integration of end-effector for 3d printing of novel uv-curable shape memory polymers with a collaborative robotic system,” in The Composites and Advance Materials Expo, 2021.