Analysis of Energy Efficiency of Mobile Robotic Platforms and Unmanned Aerial Vehicles in Hybrid Networks

Authors

  • O. V. Mykhailichenko National University «Yuri Kondratyuk Poltava Polytechnic»
  • A. S. Yanko National University «Yuri Kondratyuk Poltava Polytechnic»
  • O. I. Laktionov National University «Yuri Kondratyuk Poltava Polytechnic»

Keywords:

mobile ground robotic platforms (UGV), unmanned aerial vehicles (UAV), hybrid networks, energy efficiency, deep learning, telecommunications systems

Abstract

The paper provides a comparative analysis of the energy efficiency, functional autonomy and communication stability of mobile robotic ground platforms (UGVs) as part of hybrid telecommunications systems. The main focus is on studying the potential of UGVs as a basis for building energy-optimised and reliable next-generation networks capable of providing continuous data exchange, energy management system support and information monitoring in complex environments in both military and peacetime. Particular emphasis is placed on comparing the energy balance of ground platforms with unmanned aerial vehicles (UAVs) in order to determine the advantages of ground systems in terms of autonomous operation duration, signal stability and the possibility of using powerful antenna modules. It has been established that UGVs are characterised by low energy losses, as they do not require expenditure on maintaining altitude or stabilising their position in the air. This allows for more efficient distribution of energy resources between the motion, communication and computing systems. Due to their stable base and lack of weight restrictions, mobile ground platforms can integrate large antennas, solar panels, and energy-saving elements, this significantly increases their autonomy. The application of intelligent methods of adaptive energy consumption control using deep learning algorithms is considered. Such methods allow predicting load changes, regulating energy distribution between modules and ensuring continuity of communication even in the event of dynamic changes in network topology or the environment. It is shown that it is ground-based robotic systems that can serve as an energy-stable foundation for hybrid network infrastructure, complementing aerial elements and providing them with a stable connection in challenging conditions. This approach contributes to the creation of balanced systems in which key control, communication, and power distribution functions are implemented through autonomous ground modules capable of self-organisation and collective decision-making.

Author Biographies

O. V. Mykhailichenko, National University «Yuri Kondratyuk Poltava Polytechnic»

Post-Graduate Student of the Chair of Automation, Electronics and Telecommunications

A. S. Yanko, National University «Yuri Kondratyuk Poltava Polytechnic»

Cand. Sc. (Eng.), Associate Professor, Senior Researcher of the Chair of Computer and Information Technologies and Systems

O. I. Laktionov, National University «Yuri Kondratyuk Poltava Polytechnic»

Cand. Sc. (Eng.), Associate Professor of the Chair of Automation, Electronics and Telecommunications

References

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M. Mondal, S. Ramasamy, and P. Bhounsule, “Deep Reinforcement Learning Enabled Persistent Surveillance with Energy-Aware UAV-UGV Systems for Disaster Management Applications,” arXiv preprint, 2025. https://doi.org/10.48550/arXiv.2502.02666 .

Abstract views: 1

Published

2026-02-07

How to Cite

[1]
O. V. Mykhailichenko, A. S. Yanko, and O. I. Laktionov, “Analysis of Energy Efficiency of Mobile Robotic Platforms and Unmanned Aerial Vehicles in Hybrid Networks”, Вісник ВПІ, no. 6, pp. 78–82, Feb. 2026.

Issue

No. 6 (2025)

Section

ENERGY GENERATION, ELECTRIC ENGINEERING AND ELECTROMECHANICS

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