The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires an accurate, reliable, and robust object recognition algorithm. Vision-based guided spacecraft relative motion during close-proximity maneuvers has been consecutively applied using dynamic modeling as a spacecraft on-orbit service system. This research constructs a vision-based pose estimation model that performs image processing via a deep convolutional neural network. The pose estimation model was constructed by repurposing a modified pretrained GoogLeNet model with the available Unreal Engine 4 rendered dataset of the Soyuz spacecraft. In the implementation, the convolutional neural network learns from the data samples to create correlations between the images and the spacecraft’s six degrees-of-freedom parameters. The experiment has compared an exponential-based loss function and a weighted Euclidean-based loss function. Using the weighted Euclidean-based loss function, the implemented pose estimation model achieved moderately high performance with a position accuracy of 92.53 percent and an error of 1.2 m. The in-attitude prediction accuracy can reach 87.93 percent, and the errors in the three Euler angles do not exceed 7.6 degrees. This research can contribute to spacecraft detection and tracking problems. Although the finished vision-based model is specific to the environment of synthetic dataset, the model could be trained further to address actual docking operations in the future.
In one, docking is defined as “when one incoming spacecraft rendezvous with another spacecraft and flies a controlled collision trajectory in such a manner to align and mesh the interface mechanisms”, and defined docking as an on-orbital service to connect two free-flying man-made space objects. The service should be supported by an accurate, reliable, and robust positioning and orientation (pose) estimation system. Therefore, pose estimation is an essential process in an on-orbit spacecraft docking operation. The position estimation can be obtained by the most well-known cooperative measurement, a Global Positioning System (GPS), while the spacecraft attitude can be measured by an installed Inertial Measurement Unit (IMU). However, these methods are not applicable to non-cooperative targets. Many studies and missions have been performed by focusing on mutually cooperative satellites. However, the demand for non-cooperative satellites may increase in the future. Therefore, determining the attitude of non-cooperative spacecrafts is a challenging technological research problem that can improve spacecraft docking operations. One traditional method, which is based on spacecraft control principles, is to estimate the position and attitude of a spacecraft using the equations of motion, which are a function of time. However, the prediction using a spacecraft equation of motion needs support from the sensor fusion to achieve the highest accuracy of the state estimation algorithm. For non-cooperative spacecraft, a vision-based pose estimator is currently developing for space application with a faster and more powerful computational resource.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
A Photographic series that expresses the abstract states of myself, towards the question of existence that results from being surrounded by expectations of both surrender and freedom of expression, this series focuses on my own subjectivities in order to bring back memories of almost forgotten feelings and make them clear once more.
คณะเทคโนโลยีการเกษตร
Currently, Thailand is facing the issue of an aging agricultural workforce and a shortage of labor. The hiring process for agricultural workers is primarily based on word-of-mouth within a limited, narrow area. This may have indirect negative effects in various aspects, such as the lack of basic selection criteria (experience, skills), budget control, and hiring processes. As a result, the idea of creating a job platform specifically for farmers was conceived.Currently, Thailand is facing the issue of an aging agricultural workforce and a shortage of labor. The hiring process for agricultural workers is primarily based on word-of-mouth within a limited, narrow area. This may have indirect negative effects in various aspects, such as the lack of basic selection criteria (experience, skills), budget control, and hiring processes. As a result, the idea of creating a job platform specifically for farmers was conceived.
คณะวิทยาศาสตร์
This research will begin with a review of literature and related studies to examine existing technologies and methods for hand gesture recognition and their applications in controlling electronic devices such as drones, robots, and gaming systems. Subsequently, a hand gesture recognition system will be designed and developed using machine learning and computer vision techniques, with a focus on creating an algorithm that operates quickly and accurately, making it suitable for real-time control. The developed system will be tested and refined using various simulated scenarios to evaluate its efficiency and accuracy in diverse environments. Additionally, a user-friendly interface will be developed to ensure accessibility for all user groups. The research will also incorporate qualitative studies to gather feedback from both novice users and experts, which will contribute to further system improvements, ensuring it effectively meets user needs. Ultimately, the findings of this research will lead to the development of a functional prototype for gesture-based control, which can be applied in industries and entertainment. This will contribute to advancements in innovation and new technologies in the future.