A new algorithm for pick-and-place operation

• Published in: Industrial robot Vol. 37; no. 6; pp. 527 - 531
• Main Authors: Aminzadeh, Vahid, Wurdemann, Helge, Dai, Jian S., Reed, John, Purnell, Graham
• Format: Journal Article
• Language: English
• Published: Bedford Emerald Group Publishing Limited 01-01-2010
• Subjects: Algorithms; Assignment problem; Food; Food processing industry; Food products; Handling; Industrial equipment; Inventory management; Linear programming; Materials handling; Mathematical models; Optimization; Order picking; Robotics; Robots; Statistical analysis; Studies; Utilization; Control technology; Food industry; Robotics; Programming and algorithm theory
• ISSN: 0143-991X; 1758-5791
• DOI: 10.1108/01439911011081678

Purpose - This paper aims to represent a novel framework for optimization of robotic handling from disarray to structure where the products are randomly distributed on a surface, the initial location of the products are known (with the aid of image processing, laser position sensors, etc.) and there is a set of final positions for the products.Design methodology approach - Pick-and-place is one of the main solutions especially for the food products where the products are prone to damage, have adhesive surfaces and the grippers can be complicated. The aim of this paper is to maximize the utilization of the pick-and-place robotic system. In order to do so the handling process is modelled mathematically and the pick-and-place problem is formulated based on assignment problem where Hungarian algorithm is utilized to minimize the total distance travelled by the robot. Furthermore, a simulation program is developed to demonstrate the possible improvements of the algorithm in comparison with the existing algorithms.Findings - Utilizing the proposed algorithm can significantly increase the utilization of robots in the pick-and-place operation.Originality value - The new optimization algorithm can be applied to any industry with pick-and-place where time efficiency and maximum utilization matters.