Intersection-Free Geometrical Partitioning of Multirobot Stations for Cycle Time Optimization

Abstract

Assembly cells, where multiple robots perform sets of tasks, often face the challenge to minimize cycle time and avoid collisions. Collisions are avoided by introducing synchronization schemes among the robots, preventing shared volumes of the workspaces to be simultaneously entered. Synchronization often increases the cycle time and makes the robot programming more difficult to generate, adjust, and maintain. In this paper, we present a novel method to maximize throughput while eliminating all synchronizations among robots. We devise algorithms to minimize cycle time generating no intersection among robots at any time during their paths. First, a surrogate model for minimizing cycle time is provided and solved to optimality: each task is assigned to a robot in a way that no collision occurs. Afterward, the entire workspace is partitioned such that each robot’s workspace is separated from the others. Finally, robot paths are generated automatically in order to avoid collisions with the environment and remaining in their precomputed partitions. In the rare cases where some of these steps fail, a feedback procedure redistributing the tasks or modifying the partitions is adopted. Furthermore, since the surrogate model approximates cycle time, several solutions are generated and evaluated based on better approximations of the model. The results are convincing: computational experience on different cases from the automotive industry shows that it is possible to generate programs where the robots never intersect with each other and achieve cycle times comparable to the ones generated allowing synchronization. Note to Practitioners —Assembly cells in the automotive industries become more complex and there is a high pressure on both station throughput and robust robot programs requiring low maintenance costs. In this paper, we show that it is often possible to achieve both goals simultaneously. Specifically, we describe a method on how to generate robot programs performing predefined processing tasks, with the goal to minimize cycle time and to completely avoid synchronization among the robots. In fact, checking for interference volumes among robots increases robot programming time, leads to higher cycle time, requires reengineering when introducing new tasks, and causes restart problems when an unattended stop occurs in the cell. Therefore, we compute optimized surfaces that separate the workspaces of the robots and distribute all tasks, in order to, respectively, avoid collisions and minimize cycle time. This is done by modeling the problem as a semiassignment problem with collision constraints. The problem is then solved by combining several concepts, including combinatorial optimization and generalized Voronoi diagram. Results on different industrial test cases show the efficiency of the approach: no synchronization is needed and the robots can finish their programs in times comparable to when synchronization is allowed. As a consequence, no communication with programmable logic controllers is needed to avoid collisions between robots.