In the era of Industry 4.0, mobile robotics and autonomous vehicles have become one of the most essential research areas.
These systems can navigate, avoid obstacles, localize, and build maps (SLAM) — all of which are foundational technologies for self-driving cars, logistics robots, and drones.
The Mobile Path-Finding Robot project aims to develop a small-scale autonomous vehicle capable of:
- Moving autonomously and avoiding obstacles.
- Collecting environmental data through multiple sensors.
- Transmitting data to a computer for 2D mapping and analysis.
- Serving as a research platform for navigation, localization, and intelligent control algorithms.
- Enable the robot to move and navigate autonomously.
- Detect and avoid obstacles using ultrasonic and laser distance sensors.
- Measure motion parameters using encoder and IMU sensors.
- Transmit real-time sensor data to a computer via Wi-Fi or UART.
- Process and reconstruct a 2D environment map from collected data.
Main functional blocks:
- Sensor Block Collects environmental data from sensors.
- Signal Processing & Control Block Processes sensor signals and makes control decisions.
- Display Data (Laptop) Visualizes processed data for mapping and positioning.
- Transmission Block Sends control commands to the vehicle for movement.
Functions:
- Read wheel rotation and speed from the encoder.
- Receive obstacle information from ultrasonic and laser sensors.
- Process sensor data and make navigation decisions (turn, stop, move forward).
- Control DC motors and servo motor through the L298N motor driver.
Functions:
- Acquire data from ultrasonic, laser, IMU, and encoder sensors.
- Filter and calibrate signals (median and moving average filters).
- Transmit processed data to the computer via Wi-Fi or UART.
- On the PC, perform:
- 2D environment mapping.
- Localization of the robot based on encoder and IMU data.
