Abstract:
The human detection system in this project is implemented using the ESP32-CAM module, which enables real-time image capture and wireless video streaming. The ESP32-CAM continuously captures image frames and transmits them over Wi-Fi to an external device such as a for processing. Human detection is performed using computer vision techniques, where algorithms analyze the incoming video stream to identify the presence and position of a person within the frame. Based on the detected position, control signals are generated and sent to the ESP32 microcontroller, which interfaces with a motor driver to control the robot’s movement. If the person is detected at the center of the frame, the robot moves forward; if the person shifts to the left or right, the robot adjusts its direction accordingly. Additionally, ultrasonic sensors are used to measure the distance between the robot and obstacles, ensuring safe navigation and collision avoidance. This integration of vision-based detection and sensor-based control enables accurate and efficient human-following behavior, making the system suitable for applications such as assistive robots, surveillance systems, and smart automation.
Introduction:
The human-following robot is an intelligent robotic system designed to automatically detect and follow a person using a combination of computer vision and sensor-based navigation. With the rapid growth of robotics and automation, such systems are becoming increasingly important in applications like personal assistance, surveillance, and smart environments. In this project, the ESP32-CAM module is used for human detection, where it captures real-time images and determines whether a human is present or not. The detection result is converted into control commands that instruct the robot to either follow the detected person or remain stopped when no person is identified.
Based on these commands, the ESP32 microcontroller controls the movement of the robot using a motor driver. To guide the robot’s direction and ensure safe navigation, three ultrasonic sensors are used to measure distances in the left, center, and right directions. These sensors help the robot decide whether to move forward, turn, or stop, while also avoiding obstacles. This hybrid approach combines software-based human detection with hardware-based decision-making, making the system simple, cost-effective, and efficient. The project demonstrates how embedded systems and basic artificial intelligence concepts can be integrated to build a functional and practical human-following robot.

Objectives
1. To design and develop a human-following robot using the ESP32 and ESP32-CAM modules.
2. To implement human detection using the ESP32-CAM and generate a command.
3. To control the movement of the robot (forward, left, right, stop) based on the detection signal.
4. To use three ultrasonic sensors to determine direction and measure distance from obstacles.
5. To ensure safe navigation by implementing collision avoidance using sensor data.
6. To create a simple and cost-effective system using minimal hardware components.
7. To integrate both software (vision-based detection) and hardware (sensor-based control) into a single working system.
8. To achieve real-time response for smooth and continuous human-following behavior.