Autonomous Monocular Navigation for Robotic Vehicles using ESP32-CAM and TOF Sensor with ROS2 Integration - Miranda Neto, Milton; Cardoso, Alexandre; Moraes, Ígor Andrade; Lima, Gerson Flávio Mendes de (Anais do Congresso Latino-Americano de Software Livre e Tecnologias Abertas (Latinoware); 2025: Anais do XXII Congresso Latino-Americano de Software Livre e Tecnologias AbertasDO - 10.5753/latinoware.2025.16604, 2025)
This research presents the development and implementation of a cost-effective autonomous monocular navigation framework for robotic vehicles. The proposed system leverages an ESP32-CAM module for real-time object recognition through the YOLO algorithm, complemented by a TOF400C-VL53L1X sensor for precise distance measurements. Our approach addresses the growing need for affordable autonomous navigation solutions by integrating low-power embedded systems with established robotics frameworks. The ESP32-CAM processes visual data and transmits object detection information, including classification and distance metrics, to a Raspberry Pi 5 controller running ROS2. Experimental validation demonstrates the system’s capability to achieve reliable object detection with 78.8% precision at 3.22 FPS, while maintaining sub-2cm distance measurement accuracy across a 4-meter operational range. The complete system exhibits a 92% navigation success rate across diverse environmental scenarios, validating its practical applicability for autonomous robotic platforms.