Comparison of Energy Prediction Algorithms for Differential and Skid-Steer Drive Mobile Robots on Different Ground Surfaces

Krystian Góra, Mateusz Kujawinski, Damian Wroński and Grzegorz Granosik
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Krystian Góra: Institute of Automatic Control, Lodz University of Technology, 90-537 Lodz, Poland
Mateusz Kujawinski: Institute of Automatic Control, Lodz University of Technology, 90-537 Lodz, Poland
Damian Wroński: Institute of Automatic Control, Lodz University of Technology, 90-537 Lodz, Poland
Grzegorz Granosik: Institute of Automatic Control, Lodz University of Technology, 90-537 Lodz, Poland

Energies, 2021, vol. 14, issue 20, 1-16

Abstract: A detailed literature analysis depicts that artificial neural networks are rarely used for the power consumption estimation in the mobile robotics field. Instead, researchers prefer to develop analytical models of investigated robots. This manuscript presents a comparison of mathematical models and non-complex artificial neural networks in energy prediction tasks for differential and skid-steer drive robots which move over various types of surfaces. The results show that both methods could be used interchangeably but AI methods are more universal, do not depend on the kinematic structure of a robot and are tolerant for designers not having a complex knowledge about the system.

Keywords: differential drive mobile robot; skid-steer drive mobile robot; energy prediction algorithms; artificial neural networks (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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