The compound eye of insects has many excellent characteristics. Directional navigation is one of the important features of compound eye, which is able to quickly and accurately determine the orientation of an objects. Therefore, bionic curved compound eye have great potential in detecting the orientation of the target. However, there is a serious non-linear relationship between the orientation of the target and the image obtained by the curved compound eye in wide field of view (FOV), and an effective model has not been established to detect the orientation of target. In this paper, a method for detecting the orientation of the target is proposed, which combines a virtual cylinder target with a neural network. To verify the feasibility of the method, a fiber-optic compound eye that is inspired by the structure of the bee’s compound eye and that fully utilizes the transmission characteristics and flexibility of optical fibers is developed. A verification experiment shows that the proposed method is able to realize quantitative detection of orientations using a prototype of the fiber-optic compound eye. The average errors between the ground truth and the predicted values of the horizontal and elevation angles of a target are 0.5951 ° and 0.6748°, respectively. This approach has great potential for target tracking, obstacle avoidance by unmanned aerial vehicles, and directional navigation control.
Single-pixel imaging (SPI), which is generally based on computational imaging, has the advantages of a wide bandwidth and the ability to image objects beyond the visual field. However, the major challenge in developing SPI is the large number of illumination patterns that are required. Unlike traditional SPI that relies on random measurement patterns, the SPI method proposed in this letter involves a two-step phase shift that reduces greatly the required number of illumination patterns. Theoretical analysis shows that 6724 illumination patterns are required to reconstruct a 128 × 128-pixel image whose peak signal-to-noise ratio exceeds 30, and these can be projected in 0.3362 s with a digital micromirror device working at full speed. Compared to SPI with a four-step phase shift, half the number of illumination patterns are required. Verification experiments show that the reconstructed images can be obtained even at a sampling ratio of 20%. The proposed SPI with a two-step phase shift is an effective means of requiring fewer illumination patterns and has great potential in dynamic detection.
The planar compound eye has the advantages of simple structure and no requirement for complex relay optical elements, but the field of view (FOV) is very difficult to expand. Overcoming the limitation of FOV, especially with simple structures, is a great challenge for the development of planar compound eyes. Different from the existing designs that only considering refraction, this article proposes a catadioptric planar compound eye based on the reflection and refraction to expand the FOV. In the proposed design, the incident light from a large angle is reflected into the lenslet array by two rotationally symmetric mirrors whose surface equations are optimized by mathematical and optical softwares. The FOV of the proposed catadioptric planar compound eye theoretically can reach 96.6°, which is much wider than the opening record of 70°. Moreover, no distortion of the imaging system can be obtained theoretically in this design. Simulation results show a linearity of better than 99% for the most of the incident angles. The verification experiments show that the FOV of the proposed device can reach 90.7° while the FOV of the corresponding planar compound eye without mirrors is 41.6°. The proposed catadioptric planar compound eye has the great potential in monitoring, detection and virtual reality since the FOV has been widen significantly.
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