Path Planning for Robot Based Radial Advanced Manufacturing Using Print Space Sampling

Abstract

The world is embracing the fourth industrial revolution, Industry 4.0, which is enabling businesses to improve efficiency and optimise operations. The authors are part of a team that is researching and developing a large-scale industrial 3D printer to print smart, bespoke equipment called Gravity Separation Spirals (GSS). GSS are used in mining to separate minerals from the slurry. The printer under development employs two industrial robot arms mounted on vertical rails and the print direction is around a vertical rotating column in a radial direction. This paper presents a cost-based path planning method using print-space sampling to optimise distance error and manipulability during a printhead's radial path as it travels outwards from the central column. Manipulability, distance error and rotation error have been calculated for each sampled point and a weighted cost function has been used to determine the optimal path. Simulated results show that this method reduces the instances of print failure and improves the overall manipulability of the robot during printing.