METHODS AND TOOLS FOR MANAGING AUTONOMOUS AND SEMI-AUTONOMOUS ROBOTIC LOGISTICS DEVICES ON THE BATTLEFIELD: ANALYSIS AND POSSIBLE SOLUTIONS - ROMANIAK, OLEKSANDR; LEVUS, YEVHENIYA (Herald of Khmelnytskyi National University. Technical sciences, 2025)
This research investigates a systematic analysis of methods and technical solutions for managing autonomous and semi-autonomous robotic platforms intended for combat logistics. The study addresses the urgent need to enhance the operational reliability and effectiveness of such systems in modern warfare. The main challenges related to unstable communication channels, active electronic warfare (EW), and the high dynamics and unpredictability of the combat environment are outlined. These factors significantly complicate the task of coordination and control among robotic platforms deployed in contested areas. Based on modern technological approaches and architectural best practices, a conceptual model of adaptive control architecture is proposed. This model combines component-oriented design principles, ontological knowledge models for semantic interoperability, and message broker technologies to ensure resilient inter-platform interaction and decision-making under adverse and uncertain conditions. The developed combat logistics ontology plays a crucial role in enabling robotic platforms to make informed and autonomous decisions. It supports tasks such as route planning in dynamically changing environments, resource allocation among distributed agents, and real-time threat detection and avoidance. Methodological approaches for dynamic behavior adaptation using the MAPE-K loop (Monitor, Analyze, Plan, Execute, Knowledge) and swarm intelligence principles are proposed to increase the survivability, flexibility, and collective intelligence of control systems. The integration of these approaches allows platforms to respond appropriately to evolving mission parameters and environmental threats. The presented results are based on simulation studies and modeled combat logistics scenarios. Future research directions are outlined, including field experiments, the optimization of dynamic adaptation algorithms, cybersecurity considerations, and the development of prototype robotic platforms for operational use in military logistics operations.