Efficient Industrial Solution for Robotic Task Sequencing Problem With Mutual Collision Avoidance & Cycle Time Optimization

Abstract

In the automotive industry, several robots are required to simultaneously carry out welding sequences on the same vehicle. Coordinating and assigning welding points between robots is a manual and difficult phase that needs to be optimized using automatic tools. The cycle time of the cell strongly depends on different robotic factors such as the task allocation among the robots, the configuration solutions and obstacle avoidance. Moreover, a key aspect, often neglected in the state of the art, is to define a strategy to solve the robotic task sequencing with an effective robot-robot collision avoidance integration. In this paper, we present an efficient iterative algorithm that generates a high-quality solution for Multi-Robotic Task Sequencing Problem. This latter manages not only the mentioned robotic factors but also aspects related to accessibility constraints and mutual collision avoidance. In addition, a home-developed planner ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RoboTSPlanner</i> ) handling 6 axis has been validated in a real case scenario. In order to ensure the completeness of the proposed methodology, we perform an optimization in the task, configuration and coordination space in a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">synergistic</i> way. Comparing to the existing approaches, both simulation and real experiments reveal positive results in terms of cycle time and show the ability of this method to be interfaced with both industrial simulation software and ROS-I tools.