A Framework for Task Sequencing for Redundant Robotic Remote Laser Processing Equipment Based on Redundancy Space Sampling

This paper presents a framework for task sequencing of redundant remote laser processing equipment. The task sequencing algorithm is based on generating sets of robot configuration samples on all processing contours. The sequencing is done by using a solver for the equality constrained generalized traveling salesman problem (E- GTSP) to find the shortest path between these sets, while taking process constraints, robot redundancy and cluster connectivity into consideration. The algorithm was implemented in Matlab with interfaces to the robot simulation program V-rep and the GLKH E-GTSP solver. A test was carried out with 38 contours on a work piece with a set of angled plateaus.