A Plane Extraction Method for Embedded Computers in Mobile Robots

This paper presents a plane extraction method for embedded computers in mobile robots which typically have less power than general-desktop computers. The increasing demand on immersive technology, including VR, AR, MR, XR, has encouraged to perceive the real-world in 3D space, and so is robotics. However, a problem occurs when large amounts of data are generated, especially for the embedded computers that are usually installed in the mobile robots. Therefore, we propose the plane extraction method to compress the data into other forms suitable for the mobile robot applications. PSO-seeded region growing algorithm was applied to segment the data based on planar characteristics. The output is polygons of each detected plane that can be projected to represent the captured objects in 3D space. It is simple and easy to be applied to the embedded computers, hence less computational time. The algorithm was verified using a depth image dataset of our laboratory. Based on the experimental results, a maximum of 15.1 fps can be achieved.