Autonomous Mobile 3D Printing of Large-Scale Trajectories
Julius Sustarevas, Dimitrios Kanoulas, Simon Julier
Abstract
Mobile 3D Printing (M3DP), using printing-in-motion, is a powerful paradigm for automated construction. A mobile robot, equipped with its own power, materials and an arm-mounted extruder, simultaneously navigates and creates its environment. Such systems can be highly scalable, parallelizable and flexible. However, planning and controlling the motion of the arm and base at the same time is challenging and most deployments either avoid robot-base motion entirely or use human prescribed robot-base paths. In a previous paper, we developed a high-level planning algorithm to automate M3DP given a print task. The generated robot-base paths avoid collisions and maintain task reachability. In this paper, we extend this work to robot control. We develop and compare three different ways to integrate the long-duration planned path with a short horizon Model Predictive Controller. Experiments are carried out via a new M3DP system - Armstone. We evaluate and demonstrate our algorithm in a 250 m long multi-layer print which is about 5 times longer than any previous physical printing-in-motion system.