Abstract
This article considers the problem of optimizing the task sequences carried out by a dual-arm manipulator robot in a footwear production setting. The robot has to identify the pieces of a shoe put in a tray and pick-and-place them in a shoe mould for further processing. The shoe pieces arrive on a tray in random positions (patterns) and can be picked up in different order. In such a setting, a decision tree model is developed to recognize the pattern and predict the optimal sequence for picking the pieces up, thus, the picking and decision-making time is minimized. Two shoe models are considered for training and validating the solution proposed and the developed algorithm is applied in the real setting. There are not many studies which use the decision trees in sequencing and scheduling problems in robotics. The findings of this article show that the decision tree method has advantages in task planning in a complex environment consisting of multiple trajectories and possible collisions between robot arms.
Highlights
T HERE is an increasing trend in the current industry automation according to the pursuit of the performance in different features
An important feature is the sequence of pieces in the pick-and-place
In [6] authors develop an algorithm called Best Uniform Algorithm (BUA) to solve the problem while other solutions are based on genetic algorithm (GA) proposed by [7] and [8]
Summary
T HERE is an increasing trend in the current industry automation according to the pursuit of the performance in different features. The automation in the manufacturing lines allows the improvement of production time, precision in complex tasks, repeatability, etc. Current production processes in the shoe industry are characterized by high material consumption and low automation of production lines, but some technologies such as Knitting [1], 3DPrinting [2], Direct Injection [3] or 3DBonding [4] are increasing the level of automation in the shoe industry. An important feature is the sequence of pieces in the pick-and-place. In [6] authors develop an algorithm called Best Uniform Algorithm (BUA) to solve the problem while other solutions are based on genetic algorithm (GA) proposed by [7] and [8].
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