ابوالفضل منافي

In this thesis, a new method is presented for guiding a multi-rotor robot toward a moving target in two environments: one without obstacles and one with obstacles. This method, inspired by the proportional guidance law, is designed by considering the constraints of the problem, including preventing the robot from leaving the specified range and quickly aligning the robot's altitude with the target. In the absence of obstacles, this guidance law first generates the desired speed, and then a filter, designed to prevent the robot from leaving the allowed range, monitors the speed values to ensure the robot stays within the range. If there are obstacles in the environment, the designed guidance law predicts the collision point with the target, and then using the A* path planning method, the movement path to the collision point is calculated. The pure pursuit method is employed to follow the path, and during the robot’s movement, the out-of-bounds filter and the collision-avoidance algorithm monitor the speed commands applied to the robot. All designs in this thesis are done at a high level, and a low-level controller with multiple PID loops is used to ensure the robot follows the commands of the high-level controller. All designs implemented in the simulation environment have been tested in real-time and then implemented and eva‎luated in the real world. The results indicate that, in both the presence and absence of obstacles, the provided guidance law has successfully brought the pursuing robot close to the target while meeting the stated constraints of the problem. Furthermore, in this thesis, an extended Kalman filter is used to estimate the position and speed of the target. This filter estimates the position and speed of the target by combining radio and optical tracking data, and its performance has been validated in both simulated and real environments.

ربات‌ چند پره , قانون هدايت , برنامه‌ريزي مسير , عدم برخورد با مانع

multi-rotor robot , Guidance law , path planning , Obstacle Avoidance

Abolfazl Manafi

Dr saeid Shamaghdari