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

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...

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Bibliographic Details
Published in:Energies (Basel) 2021-10, Vol.14 (20), p.6722
Main Authors: Góra, Krystian, Kujawinski, Mateusz, Wroński, Damian, Granosik, Grzegorz
Format: Article
Language:English
Subjects:
Algorithms
Approximation
artificial neural networks
Comparative analysis
differential drive mobile robot
Efficiency
Energy
energy prediction algorithms
Friction
Kinematics
Mathematical models
Neural networks
Power consumption
Robots
Sensors
skid-steer drive mobile robot
Task complexity
Velocity
Wheels
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Summary: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en14206722