Search

Motion cueing algorithms (MCA) are often applied in the motion simulators. In this paper, a nonlinear optimal MCA, taking into account translational and rotational motions of a simulator within its physical limitation, is designed for the motion platform aiming to minimize human’s perception error in order to provide a high degree of fidelity. Indeed, the movement sensation center of most MCA is placed at the center of the upper platform, which may cause a certain error. Pilot’s station should be paid full attention to in the MCA. Apart from this, the scaling and limiting module plays an important role in optimizing the motion platform workspace and reducing false cues during motion reproduction. It should be used along within the washout filter to decrease the amplitude of the translational and rotational motion signals uniformly across all frequencies through the MCA. A nonlinear scaling method is designed to accurately duplicate motions with high realistic behavior and use the platform more efficiently without violating its physical limitations. The simulation experiment is verified in the longitudinal/pitch direction for motion simulator. The result implies that the proposed method can not only overcome the problem of the workspace limitations in the simulator motion reproduction and improve the realism of movement sensation, but also reduce the false cues to improve dynamic fidelity during the motion simulation process.

The classical washout algorithm had fixed gains and manually constructed filters, so that it led to poor adaptability. Furthermore, it lost the sustained acceleration cues of high- and mid-frequency in cross-over (tilt-coordination) channel, and the acceleration of cross-over frequency was also limited by angular velocity limiter, so the false cues in flight simulation process were clearly perceived by pilots. The paper studied the characteristics of the classical washout algorithm and flight simulator motion platform, tried to redesign the source of cross-over acceleration channel and translation acceleration channel, and transferred the part of cross-over acceleration that was unsimulated sustained acceleration to translation acceleration channel. Comparisons were mainly made between classical washout algorithm and revised algorithm in a longitudinal/pitch direction. The evaluation was based on the implementation of human vestibular perception system. The results demonstrated that the revised algorithm could significantly reduce the phase lag, and improved the spikes tracking performance. Furthermore, sensory angular velocity and the error of sensory acceleration were strictly controlled within the threshold of human perception system, and the displacement was a little broader than the classical washout algorithm. Therefore, it was proved that the new algorithm could diminish the filters parameters and heighten the self-adaptability for the washout algorithm. In addition, the magnitude of false cues was remarkably reduced during flight simulator, and the workspace utilization of the motion platform was developed by “closed-loop” control system.

Based on compressive sensing, multi-views light field images were reconstructed both simulating and physical implementing. LF-image depth estimation with multi-clue fusion was realized. And multi-view true color images were generated synthesized though spectral data.

3D reconstruction is studied by the two different methods with focus stack. Results show the way of lytro camera surpass compression mask.The main reason is whether the focal plane depth variation meets the actual scene.

Camera calibration is one of the indispensable processes to obtain 3D depth information from 2D images in the field of computer vision. Camera self-calibration is more convenient and flexible, especially in the application of large depth of fields, wide fields of view, and scene conversion, as well as other occasions like zooms. In this paper, a self-calibration method based on two vanishing points is proposed, the geometric characteristic of disappear points formed by two groups of orthogonal parallel lines is applied to camera self-calibration. By using the vectors’ orthogonal properties of connection optical centers and the vanishing points, the constraint equations on the camera intrinsic parameters are established. By this method, four internal parameters of the camera can be solved though only four images taken from different viewpoints in a scene. Compared with the two other self-calibration methods with absolute quadric and calibration plate, the method based on two vanishing points does not require calibration objects, camera movement, the information on the size and location of parallel lines, without strict experimental equipment, and having convenient calibration process and simple algorithm. Compared with the experimental results of the method based on calibration plate, self-calibration method by using machine vision software Halcon, the practicability and effectiveness of the proposed method in this paper is verified.