CUDA-Based Method to Boost Target Performance Evaluation of Space Systems for Automatic Mobile Object Identification and Localization

Robot Target Localization and Visual Navigation Based on Neural Network

“…For example, this paper involves the world coordinate system and the camera coordinate system, by finding two 3D point set space, relative transformation relationship to the unified under the same coordinate system (usually refers to the world coordinate system); the purpose is to find in the global coordinate system to obtain the current view of the relative position of the camera and the direction, his appearance, makes the intersection area completely overlap between the two, the process said for registration. In the calculation process, registration is to find the 4 4 rigid transformation matrix T that makes the intersection area between the two points converge completely coincide and to calculate the optimal rigid body transformation by repeatedly selecting the corresponding point pairs until the accuracy requirements of convergence are met [5,6,8]. The rigid transformation matrix T mainly includes the aforementioned translation vector T, rotation matrix R, perspective transformation vector V, and scale factor S, because point cloud data is obtained according to a certain number of continuous pictures.…”

“…Humans can quickly and accurately capture and integrate a large amount of element information in the target scene by using their eyes, which is a developed visual system. However, for robots, the target scene is rich in information due to the complexity of visual problems Due to the complexity of computation, the present robot vision system is still difficult to achieve the cognitive recognition ability of human eyes [5,6]. For a robot to the development of the intelligent visual perception system is an important part of the robot, which is one of the main sources of robot perception surrounding environment, whether the rapid and effective use of visual information will directly affect the interaction of the robot, in the environment of the variability, and randomness is particularly important.…”