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Abstract

The paper introduces the distributed framework for determining the shortest path of robots in the logistic applications, i.e. the warehouse with a swarm of robots cooperating in the Real- Time mode. The proposed solution uses the optimization routine to avoid the downtime and collisions between robots. The presented approach uses the reference model based on Dijkstra, Floyd- Warshall and Bellman-Ford algorithms, which search the path in the weighted undirected graph. Their application in the onboard robot’s computer requires the analysis of the time efficiency. Results of comparative simulations for the implemented algorithms are presented. For their evaluation the data sets reflecting actual processes were used. Outcomes of experiments have shown that the tested algorithms are applicable for the logistic purposes, however their ability to operate in the Real-Time requires the detailed analysis.
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Bibliography

[1] Mobile Robot Platforms, Shuttle Automated Storage and Retrieval Systems, Industrial Robotic Manipulators, and Gantry Robots: Global Market Analysis and Forecasts, Informa PLC, https://www.tractica.com/research/warehousing-and-logistics-robots/
[2] J. Miklinska, “Trends in the logistic market and warehouses for logistics service providers-experiences from Poland,” Economic and Social Development: Book of Proceedings, 2020, 193-202.
[3] M. Khamphroo, N. Kwankeo, K. Kaemarungsi, K. Fukawa, “MicroPython-based educational mobile robot for computer coding learning,” 2017 8th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES), Chonburi, 2017.
[4] K. Dokic, B. Radisic, M. Cobović, “MicroPython or Arduino C for ESP32 - Efficiency for Neural Network Edge Devices,” Springier, 2020, pp.33-34, https://doi.org/10.1007/978-3-030-43364-2_4.
[5] N. Deo, “Graph theory with applications to engineering and computer science,” Englewood Cliffs, NJ: Prentice-Hall, 1974.
[6] G. Laporte, ”The traveling salesman problem: An overview of exact and approximate algorithms,” EJOR, 1992, Vol.59, pp. 231-247.
[7] Lu Feng, “Shortest path algorithm: Taxonomy and Advance in Research”, Acta Geodaetica et Cartographica Sinica, vol. 30, no. 3, pp. 269-275, 2001.
[8] D. Dobrilovic, V. Jevtic, I. Beker, Z. Stojanov, “Shortest-path based Model for Warehouse Inner Transportation Optimization” in 7th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)
[9] Y. Liu, T. M. Vitolo, “Graph Data Warehouse: Steps to Integrating Graph Databases Into the Traditional Conceptual Structure of a Data Warehouse,” 2013 IEEE International Congress on Big Data, 2013, pp. 433-434, https://doi.org/10.1109/BigData.Congress.2013.72
[10] H.Y. Jang, J.U. Sun, “A Graph Optimization Algorithm for Warehouses with Middle Cross Aisles,” Applied Mechanics and Materials, 2011, 145. 354-358, https://doi.org/10.4028/www.scientific.net/AMM.145.354.
[11] B.D. Acharya, M.K. Gill, “On the Index of Gracefulness of a Graph and the Gracefulness of Two-Dimensional Square Lattice Graphs, ” Indian J. Math., 1981, 23, 81-94.
[12] T.H. Cormen, C.E. Leiserson, and R.L. Rivest, “Introduction to algorithms,” MIT Press, 1994.
[13] Warehouse material flows and flow charts, https://www.mecalux.co.uk/warehouse-manual/warehouse-design/warehouse-material-flowchart
[14] A. Niemczyk et al., “Organizacja i monitorowanie procesów magazynowych,” Instytut Logistyki i Magazynowania, 2014.
[15] A. Szymonik, D. Chudzik, “Logistyka nowoczesnej gospodarki magazynowej,” Difin, 2018.
[16] B. Mbakop A. Kevine, “The Effectiveness of ABC Cross Analysis on Products Allocation in the Warehouse,” 2018, January – February, Vol. 5, Issue 1, pp: 11-30.
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Authors and Affiliations

Tomasz Markowski
1
Piotr Bilski
2
ORCID: ORCID

  1. Lukasiewicz – Institute of Logistics and Warehousing, Poland
  2. Warsaw University of Technology, Poland
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Abstract

This paper presents an alternative approach to the sequential data classification, based on traditional machine learning algorithms (neural networks, principal component analysis, multivariate Gaussian anomaly detector) and finding the shortest path in a directed acyclic graph, using A* algorithm with a regression-based heuristic. Palm gestures were used as an example of the sequential data and a quadrocopter was the controlled object. The study includes creation of a conceptual model and practical construction of a system using the GPU to ensure the realtime operation. The results present the classification accuracy of chosen gestures and comparison of the computation time between the CPU- and GPU-based solutions.

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Authors and Affiliations

Marek Wodziński
Aleksandra Krzyżanowska
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Abstract

The purpose of the work presented here is a comparative analysis of two methods of solving the problem of optimizing the working time and path length of operators for manual harvesting of raspberries over an area of one hectare. An analytical solution is a method of solving mathematical problems based on finding an exact formula that describes a phenomenon or process. A simulation solution is the opposite of a numerical solution, which is based on calculating an approximation using statistical methods. An analytical and simulation approach will be presented to show how to calculate the number of workers needed, the minimum working time and the length of the path taken by raspberry fruit pickers. The results obtained for the two methods are compared.
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Authors and Affiliations

Ireneusz KACZMAR
Tamás BANYAI

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