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This paper presents a structured experimental framework for evaluating the performance of an autonomous rover designed for operation in hazardous and remote environments. The proposed methodology encompasses systematic testing of key subsystems, including motion control, sensor accuracy, autonomous navigation, and wireless communication. The rover, equipped with an ESP32 microcontroller, Raspberry Pi 4/5, environmental sensors, and a vision system, will undergo rigorous validation in both controlled indoor settings and real-world outdoor conditions. Motion control experiments will assess the precision of PID-based motor regulation across various terrains, while sensor performance tests will analyze the effectiveness of data filtering techniques in enhancing measurement reliability. Additionally, autonomous navigation and vision system evaluations will focus on object detection, obstacle avoidance, and adaptive path planning under dynamic conditions. Wireless communication trials will examine latency and connectivity stability over extended operational distances. The integrated system assessment will simulate realistic scenarios to verify overall functionality and identify potential areas for improvement. Findings from these experiments will inform future enhancements, including advanced machine learning models and expanded sensory capabilities, to further optimize the rover’s autonomous performance and adaptability in complex environments.

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Remote-Controlled Vehicle with Integrated Environmental Vision and Sensing Systems

  • 会议论文

  • 发表日期：

    2026年

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  • Mladen Milić,
  • Milovan Medojević

摘要

This paper presents a structured experimental framework for evaluating the performance of an autonomous rover designed for operation in hazardous and remote environments. The proposed methodology encompasses systematic testing of key subsystems, including motion control, sensor accuracy, autonomous navigation, and wireless communication. The rover, equipped with an ESP32 microcontroller, Raspberry Pi 4/5, environmental sensors, and a vision system, will undergo rigorous validation in both controlled indoor settings and real-world outdoor conditions. Motion control experiments will assess the precision of PID-based motor regulation across various terrains, while sensor performance tests will analyze the effectiveness of data filtering techniques in enhancing measurement reliability. Additionally, autonomous navigation and vision system evaluations will focus on object detection, obstacle avoidance, and adaptive path planning under dynamic conditions. Wireless communication trials will examine latency and connectivity stability over extended operational distances. The integrated system assessment will simulate realistic scenarios to verify overall functionality and identify potential areas for improvement. Findings from these experiments will inform future enhancements, including advanced machine learning models and expanded sensory capabilities, to further optimize the rover’s autonomous performance and adaptability in complex environments.