Path Planning for Mobile Robots Applied in the Distribution of Materials in an Industrial Environment
This paper presents a new approach to solve the problem of logistics in a factory by automating the distribution of materials. Thus, a general algorithm of path planning is applied for the physical distribution of the production area, in the case of Power
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[email protected] 2 Escuela Politécnica Nacional, Quito, Ecuador
{allison.rodriguez,danilo.chavez,oscar.camacho}@epn.edu.ec
Abstract. This paper presents a new approach to solve the problem of logistics in a factory by automating the distribution of materials. Thus, a general algorithm of path planning is applied for the physical distribution of the production area, in the case of PowerTech Transformer Factory and Man Busses Factory. A modification to the basic RRT algorithm is used to attain the minimum distance to be followed when exploring the entire work area. Accordingly, simulated results demonstrate how the mobile robots distribute the materials from the warehouse to each workstation and return to the warehouse. Keywords: Mobile robot · RRT algorithm · Path planning · Coordinate system · Lyapunov control
1 Introduction Large factories have achieved a high percentage of automation of their processes. When correctly implemented, the delivery of materials might be 100% automatic. As a result, these factories register a reduction in the amount of time need to distribute the materials from the warehouse to each work station, increasing their productivity by decreasing product handling. It also prompts the possibility of a continuous supply in the production lines, improves efficiency in the use of a transport fleet, enhancing speed and stability when stowing over other products as well as increases the safety of the personnel involved in the handling of goods (Sun et al. 2010). However, there are many challenges still to be properly solved, one of which is the use of mobile robots for internal logistics. Mobile robots are generally used in several applications such as exploration, research, trajectory tracking, among others. here exists a wide array of uses for these robots to load and offload materials (Nascimento Martins et al. 2008). For instance, (Grijalva et al. 2018) proposed a path planning for mobile robots based on the physical disposition of the factory where the robots distributed raw material, or as (Sun et al. 2010) presented a decentralized controller of autonomous robots for intralogistics. A prime example is © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. Botto-Tobar et al. (Eds.): ICCIS 2020, AISC 1273, pp. 323–337, 2021. https://doi.org/10.1007/978-3-030-59194-6_27
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factories at the forefront of the distribution of materials such as KUKA (“KMP 1500,” 2017), MIR (“The future in motion,” 2018) or Amazon Robotics. The control of several mobile robots becomes highly complex due to the required coordination among them, the creation, the following, and the navigation of paths in the area (Andaluz and Andaluz 2012). Hence, an analysis of a dynamic model is necessary to perform the coordination, the validation of constants, and the nonlinear control for trajectory tracking of mobile robots (Nascimento Martins et al. 2008). (Sabattini et al. 2015) introduced an analysis of the dynamic model
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