Obstacle Avoidance Autonomous Robot: An Implementation of Fuzzy Inference System

Abstract

Designing of autonomous navigation is very complex and challenging. The main motive of the proposed research was to construct an autonomous robot which has a proficiency to move in unpredictable and dynamic environments, and for that reason the robot has to sense the environment and lug out the required tasks irrespective of any hindrances in its working area. Applications of autonomous mobile robots can include espionage, underground mining, military operations, driverless transportation, identification of intrusion and protect missions, etc. Several various approaches have been critiqued to perform such operability of robot but results proved that the Fuzzy logic found to be the best for this kind of robotics operations because it has the capability to respond meritoriously to the complex inputs. To refrain and bypass the obstacles accurately and to attain the destination under various contour of obstruction in surroundings, a fuzzy logic approach has been studied and carried out to advance the motion of robot vigorously with less false alarm rate using ‘If-Then’ basic principle fuzzy inference norms and defuzzification procedure for the accurate and precise path planning and navigation of autonomous robot. The unmanned robot was furnished with sensors (ultrasonic HC-SR04) which has the aptitude to detect the scope of hindrances on the premise of how close or far the impediment is. To achieve this a solitary board PC was utilized, to be specific Raspberry-Pi 2 model b which takes the inputs from the sensors and maintain a strategic distance from the snags set in their way lastly proceeds onward. Results proved that our designed robot is a cost-effective solution performed better than the other techniques.