Real-time application of swarm and evolutionary algorithms for line follower automated guided vehicles: a comprehensive
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RESEARCH PAPER
Real‑time application of swarm and evolutionary algorithms for line follower automated guided vehicles: a comprehensive study Mahmoud Bakhshi Nejad Beigzadeh Mahaleh1 · Seyed Abolghasem Mirroshandel2 Received: 11 January 2020 / Revised: 13 September 2020 / Accepted: 18 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract One of the most economical forms of automated guided vehicles (AGV) is a vision-based line follower. A line follower uses machine vision to extract the path shape from the captured image and follows it. Among many methods for path detection, some studies suggested using the real-time application of meta-heuristic population-based algorithms for visual line follower AGV. Generally, Swarm Intelligence and Evolutionary Algorithms are not well suited for real-time applications as they need generations to evolve. For this reason, a comprehensive study is presented to find the best solutions to this particular application. Artificial Bee Colony, Genetic Algorithm, Harmony Search, Imperialist Competitive Algorithm, and Particle Swarm Optimization were studied with three proposed objective functions that could assist path shape detection. The fastest and most reliable solution is optimized and tested on a real AGV platform. The AGV designed for this research has an independent onboard Raspberry Pi 3 with an ARM processor and it is capable of traversing the track fast and reliably. Furthermore, the proposed system does not require edge detection or down-sampling on captured images. Additionally, our newly developed direction inferring technique, the Triangle Closest Midpoint, enables the AGV to find its path even with faulty or incomplete input. As a result, a novel real-time meta-heuristic line follower AGV is presented in this research. Keywords Swarm intelligence · Evolutionary algorithm · Line follower · Machine vision · Automated guided vehicle
1 Introduction The demand for automation is rising on a daily basis. Machines are capable of performing difficult tasks under harsh conditions where no human can endure. Considering the automation of a task, the goal is to build a machine to do the job without human intervention. Automated machines have to be much faster than their human counterparts, more precise, deliver the same results, and be relentless at minimum maintenance cost. However, creating a fully independent machine capable of fulfilling the required tasks by itself is fairly complex and still requires huge amounts of research to this date. A better solution is to provide some sort of * Seyed Abolghasem Mirroshandel [email protected] Mahmoud Bakhshi Nejad Beigzadeh Mahaleh [email protected] 1
Department of Computer Science, University of Guilan, University Campus 2, Rasht, Iran
Department of Computer Engineering, University of Guilan, P.O. Box: 1841, Rasht, Iran
2
guidance for the machine by manipulating the environment where the machine is supposed to work. This approach reduces the complexity of the problem at hand
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