Optimization of the pick-and-place sequence of a bimanual collaborative robot in an industrial production line

Abstract

This paper focuses on optimising pick-and-place tasks performed by a dual-arm collaborative robot in a specific shoe manufacturing industry environment. The robot must identify the pieces of a shoe placed on a tray, pick them up, and place them in a shoe mold for further processing. The shoe pieces arrive on the tray in random positions and angles and can be picked up in a different order. Optimising these tasks could increase the assembly speed of each unit and improve shoe production. To achieve this goal, a mathematical model based on binary integer linear programming (BILP) has been developed. This model determines the optimal sequence for picking and placing the shoe pieces in the mold, thus minimising the time required for picking and decision-making. The effectiveness of this approach has been tested using two 3-piece unit shoe models: one for training and another for validation. These models encompass a total of 500 trays. An analysis of the results reveals that BILP offers advantages for task motion planning in complex environments with multiple trajectories and the potential for collisions between arms. The model’s generalizability to shoes with n assembly pieces further confirms its robustness for various piece counts.

Development of a Tool to Manipulate Flexible Pieces in the Industry: Hardware and Software

“…The findings in [10] and other similar research underscores the importance of this technology in the contemporary textile industry. It is also relevant to mention the study [11,12] which highlights the time optimization in pick-and-place applications in footwear production. Another study [13] was conducted to optimize the execution of simultaneous tasks by multiple robots in a shared space.…”