On March 2, at 5:00 PM, the 4th seminar in the CSIE Seminar Series took place, focusing on the development of a wheeled robotic platform integrating Arduino, ESP32, and Raspberry Pi 4 with various sensors and communication modules to program and control autonomous robot operation.

The seminar was led by CSIE junior researcher Hayk Simonyan, who walked attendees through the full hardware stack — from DC brushed motors and lithium battery management systems to Bluetooth communication, PWM-based motor control, and computer vision with OpenCV. During the discussion, footage from experiments carried out across multiple project stages was presented, and the seminar concluded with a live demonstration of the practical results on the actual working robotic device.

Following our Seminar 4 recap, here is a closer look at the experimental footage presented during the session — a compilation of results achieved across all three project stages of the wheeled robotic platform. https://www.facebook.com/reel/1608988680430055

✔️Project 1 — Arduino + Bluetooth + MPU6050: The robot was controlled wirelessly via Bluetooth using an HC-05 module connected to an Arduino Pro Micro, with motion data streamed from the MPU6050 IMU sensor.

✔️Project 2 — ESP32 + Phone UI: The platform was upgraded with an ESP32 microcontroller, enabling control through a custom mobile interface over Bluetooth — demonstrating smoother, more responsive motion management.

✔️Project 3 — Raspberry Pi 4: Advanced stage of the project, comprising three distinct sub-projects, each exploring a different aspect of autonomous robotic control.

◾Project 3.1 | Raspberry Pi 4 + PC (Wi-Fi/SSH): The Raspberry Pi 4 was integrated into the robotic platform and connected to a PC over Wi-Fi via SSH, enabling wireless command-based control of the robot's motion in real time.

◾Project 3.2 | Raspberry Pi 4 + Camera Module 3 + OpenCV: A Raspberry Pi Camera Module 3 was added to the platform, and OpenCV-based computer vision was implemented — enabling real-time visual processing including person detection and tracking directly on the robot.

◾Project 3.3 | Raspberry Pi 4 + LiDAR + ROS 2 (ongoing): The most ambitious sub-project, aimed at implementing autonomous mapping, localization, and navigation using an RPLIDAR sensor and ROS 2. This sub-project is currently in its active working phase, and experiments will continue iteratively as the remaining hardware and software components are progressively integrated.