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Regression-Based Modeling for Energy Demand Prediction in a Prototype Retail Manipulator

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  • Piotr Kroczek

    (Department of Fundamentals of Machinery Design, Silesian University of Technology, 18a Konarskiego Street, 44-100 Gliwice, Poland
    Hemitech Sp. z o.o., 44-122 Gliwice, Poland)

  • Krzysztof Lis

    (Department of Machine Technology, Silesian University of Technology, 18a Konarskiego Street, 44-100 Gliwice, Poland)

  • Piotr Przystałka

    (Department of Fundamentals of Machinery Design, Silesian University of Technology, 18a Konarskiego Street, 44-100 Gliwice, Poland)

Abstract

The present study proposes two regression-based models for predicting the energy consumption of a four-axis prototype retail manipulator. These models are developed using experimental current and voltage measurements. The Total Energy Model (TEM) is a method of estimating energy per trajectory that utilizes global motion parameters. In contrast, the Power-to-Energy Model (PEM) is a technique that reconstructs energy from predicted instantaneous power. It has been demonstrated that both models demonstrate high levels of predictive accuracy, with mean absolute percentage error (MAPE) values ranging from 1 to 1.5%. These models are well-suited for implementation in hardware-constrained environments and for integration into digital twins.

Suggested Citation

  • Piotr Kroczek & Krzysztof Lis & Piotr Przystałka, 2025. "Regression-Based Modeling for Energy Demand Prediction in a Prototype Retail Manipulator," Energies, MDPI, vol. 18(14), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:14:p:3858-:d:1705764
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