Master’s Thesis Explores Optimal Pathfinding for Mobile Robots Using AI
The Department of Electrical Engineering at the University of Technology awarded a master’s degree to Roa Jawad Abdul-Kadhim for her thesis titled “Optimum Path Finding for Mobile Robot Based on Artificial Intelligent Systems.”
The research focuses on finding the most efficient path for mobile robots to reach their targets in the shortest possible time, leveraging advancements in robotics and artificial intelligence (AI). The study explored two AI techniques: Fuzzy Logic and Particle Swarm Optimization (PSO), for path optimization.
In the practical implementation, the researcher used:
- Three ultrasonic sensors for obstacle detection.
- A Mini FPGA Altera board (Cyclone IV).
- A DC motor controlled via an H-Bridge driver.
The mobile robot continuously measures distances from three directions (front, right, and left) using the ultrasonic sensors. By comparing these measurements with a pre-set threshold of 30 cm, the robot determines its movement, avoiding obstacles and choosing the optimal path to reach its target. The research demonstrated a 16% error rate when comparing algorithm performance to real-world hardware results.
The examination committee included:
- Asst. Prof. Dr. Hasan Wariush Halo (Chair)
- Asst. Prof. Dr. Ayman Dawood Salman (Member)
- Asst. Prof. Sabah Abdul-Hassan Kataa (Member)
- Asst. Prof. Dr. Iyad Ibrahim Abbas (Supervisor)
- Dr. Sundus Dhameed Hassan (Supervisor)
