Fuzzy Logic and PID Tuning-Based Optimization of 3-DoF Hexapod Robot Motion for Disaster Management (SAR)

Robust and accurate robotic platform mobility is crucial for exploring disaster-affected areas during Search and Rescue (SAR) operations. This research focuses on the optimization of motion control for a 3-DoF hexapod robot, aiming to enhance its stability, mobility, and obstacle avoidance capabilities for disaster management. The proposed control system integrates Proportional-Integral-Derivative (PID) tuning for precise motor control with a fuzzy logic framework for adaptive decision-making in complex environments. The control architecture is built upon a validated kinematic model, utilizing forward and inverse kinematics to command leg and body movements. System performance was verified through both simulation and physical experiments. Simulations confirmed the accuracy of the kinematic models, the stability of the generated tripod gait, and the robot’s ability to follow complex 3D trajectories with high fidelity. In physical trials, the hexapod prototype successfully navigated a test track featuring significant obstacles, including walls and rocks. The testing findings show notable improvements in motion control, demonstrating that the intelligent control system makes the hexapod robot a more effective and reliable tool for SAR applications. This work underscores the potential of intelligent robotic systems to significantly improve the efficiency of disaster response efforts.