Abstract
This research investigates the development of a custom hybrid operating system (OS) for a Mars rover experimental prototype using the Raspberry Pi platform. Focusing on operating system optimization, the work enhances computational efficiency, real-time responsiveness, and AI integration. Key innovations include overclocking (boosting CPU performance by 28%), custom threading (reducing task scheduling latency by 22%), and networking improvements for stable remote operation. Codec refinements and framework adaptations improved real-time video analysis throughput by 30%. Integration of a Power-over-Ethernet (PoE) HAT enhanced thermal regulation and stabilized system runtime. Experimental results show the customized OS effectively supports intensive tasks such as image processing, sensor data acquisition, and edge AI workloads. The findings demonstrate a scalable, modular OS framework for real-time vision systems and intelligent robotics in resource-constrained environments.