DEVELOPMENT OF FUZZY LOGIC AND TKINTER SUPPORTED SEMI-AUTONOMOUS MOBILE SEARCH AND RESCUE ROBOT SOFTWARE

The speed of technological changes in our rapidly developing world is an undeniable fact. With the contributions of science fiction novels and movies, expectations from the robotic universe are increasing at the same rate. Technological products are developed to meet the needs of humanity, or technological advancements lead to new needs. This study, prepared with the concern of how to be more beneficial to humanity, aims to help reduce earthquake disaster damages. The ROSbot 2.0 robot based on the Robot Operating System of the Husarion company was reprogrammed with a new low-cost approach to contribute to coarse search operations in search and rescue efforts using the Gazebo simulator. In the study, the Python programming language was used. A window reflecting the camera data was created with the Tkinter module, and a canvas was developed on this window where objects' lengths could be measured by drawing with the mouse. The suitability of the gap measurements in coarse search operations was calculated using fuzzy logic. Additionally, with the fuzzy logic-supported autonomous driving code, obstacle avoidance and progress towards the target tasks were successfully performed. During autonomous driving, speed and rotation angle values were obtained with the help of fuzzy logic according to laser sensor data to enable the robot to quickly adapt to dynamic conditions. Thus, it was seen that professional search and rescue teams could avoid harm in new collapses caused by fires, aftershocks, etc., that might occur in the wreckage areas, rescuing the victims faster and helping this robot sent on a reconnaissance mission to assist in dividing the wreckage area into sectors.