This repo contains code of Ground Robots.
This project aims to enable ground robots autonomously cover a designated area. Ground robots are expected to generate an optimal path to cover a designated outdoor area without missing any parts, while avoiding people, pets, and obstacles in the area. Therefore, artificial intelligent approaches and algorithms for autonomous coverage of designated areas, and robotic obstacle avoidance methods are needed.
Intelligent approaches and algorithms are designed for autonomous coverage of designated areas, and robotic obstacle avoidance methods. By using Matlab, the experimental robot is now able to recognize a designated area's boundary and the obstacles inside it. Aside from that, it will autonomously plan and successfully execute the motion of the robot for complete coverage, while avoiding obstacles.
Intelligent approaches and algorithms are designed for autonomous coverage of designated areas, and robotic obstacle avoidance methods. By using Matlab, the experimental robot is now able to recognize a designated area's boundary and the obstacles inside it. Aside from that, it will autonomously plan and successfully execute the motion of the robot for complete coverage, while avoiding obstacles.
Since ground robots are expected to generate optimal paths while avoiding obstacles, safe points and obstacle points need to be recognized at the beginning. Afterwards, optimal paths are generated by calculating shortest distance between points within a specific range by using algorithms designed earlier.
D.H. thanks her supervisors Dr. Aygun in Department of Computer Science and Dr. Fahimi in Department of Mechanical Engineering for their professionalism, patience and passion. Also, D.H. thanks the RCEU staff and the Office of Research & Economic Development at UAH.