AI Summary & Key Takeaways
AI InsightThe experimental results, considering the optimal path lengths and execution time, show that the proposed design is more effective and faster to generate the shortest path.
📌 3 Key Takeaways
Abstract
One of the most studied problems in robotics is robot path planning. Many strategies have been invented. Image processing and machine vision technology also have been utilized in this regard. Studies are still underway to improve path planning methods. This paper proposes an implementing visual servoing-based technique using the A* algorithm to achieve efficient searching capabilities of path planning in complicated maps with a combination of LabVIEW and MATLAB software. The proposed algorithm is divided into three parts. Firstly, the environment model or robot motion environment is conducted. In this stage, the visual information extracted from a single ceiled camera. Secondly, the position and orientation of the objects (robot, obstacles etc.) under the visibility of the camera are generated from visual information. Thirdly, the A* algorithm is used as a path planning method. This algorithm is not guaranteed the generated path to be safe and desirable with obstacle-free. To solve this problem image processing techniques are utilized. This gives an effective improvement and high performance to A* in a complex environment and gives a safe path as a comparison to the traditional version of A*. The experimental results, considering the optimal path lengths and execution time, show that the proposed design is more effective and faster to generate the shortest path.