Empirical corroboration of an earlier theoretical resolution to the UV paradox of insect polarized skylight orientation

Ultraviolet bionic compass method based on non-ideality correction and statistical guidance in twilight conditions

Bionic polarization compass is a fascinating subject in the navigation domain. However, the polarization navigation accuracy is severely degraded by the influence of city glow at dusk. Therefore, we proposed an ultraviolet bionic compass method based on non-ideality correction and statistical guidance. A non-ideal polarization imaging model was established to correct the system detection error. A meridian extraction algorithm based on the statistical properties of solar direction vectors was proposed for accurate heading calculation. The proposed algorithm was demonstrated experimentally and reduced the heading error to approximately 1°, which shows strong anti-interference performance against urban glare.

Passive Polarized Vision for Autonomous Vehicles: A Review

This review article aims to address common research questions in passive polarized vision for robotics. What kind of polarization sensing can we embed into robots? Can we find our geolocation and true north heading by detecting light scattering from the sky as animals do? How should polarization images be related to the physical properties of reflecting surfaces in the context of scene understanding? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying future directions in passive polarized vision for robotics. After an introduction, three key interconnected areas will be covered in the following sections: embedded polarization imaging; polarized vision for robotics navigation; and polarized vision for scene understanding. We will then discuss how polarized vision, a type of vision commonly used in the animal kingdom, should be implemented in robotics; this type of vision has not yet been exploited in robotics service. Passive polarized vision could be a supplemental perceptive modality of localization techniques to complement and reinforce more conventional ones.

Solar position detection method by bionic polarized light compass

To address the needs of polarized light navigation for accurate position information of feature points in the sky, an accurate solar position detection method based on an all-sky polarization pattern imaging system is proposed. Unlike the traditional spot-based solar position detection method, this method uses the polarization information inherent in the atmosphere to accurately measure solar position. This approach is characterized by simple detection, high accuracy, and wide application range. The optical acquisition system is composed of three miniature large-field camera modules and polarizers, which enables a more compact structure, smaller size, and lesser height. Based on this principle, the solar position solution algorithm was simulated and then verified in various weather environments using the optical acquisition system built as part of this study. Solar position was detected at different moments on the same day in clear weather, and the accuracy of the measured solar altitude and azimuth angles was 0.024° and 0.03°, respectively. The accuracy of the measured solar altitude and azimuth angles was 0.08° and 0.05°, respectively, when the sun was shielded by high-rise buildings and 0.3° and 0.1° when the sun was shielded by branches and tree leaves. Aerosol concentrations exceeding a certain amount destroyed the Rayleigh distribution pattern of polarized light, thus affecting solar position detection accuracy. It is concluded that this novel detection method can not only meet the needs of polarized light navigation for solar position, but also provide a new exploration idea for enthusiasts who are eager to explore the mysteries of the universe.

Ultraviolet-visible light compass method based on local atmospheric polarization characteristics in adverse weather conditions

Bionic polarization navigation has attracted extensive attention because of its strong anti-interference performance and no accumulation of errors over time. However, very few studies have fully considered the influence of adverse weather conditions such as cloudy and overcast weather, which play a key role in navigation accuracy. Therefore, we propose an adaptive ultraviolet-visible light compass method based on local atmospheric polarization characteristics applicable to various weather conditions. The proposed method transforms the heading determination problem into a multiclassification problem by using a weather recognition technique. Ultraviolet detection is used to weaken the depolarization effect of cloud particles and to obtain more accurate skylight polarization patterns. Then, on the basis of screening effective data, the sun direction vector is calculated by using the electric vector direction and is finally combined with the astronomical calendar to achieve navigation. The experimental results confirm that, compared to the other methods, the designed algorithm can suppress the interference of clouds better and adapt to complex weather conditions. Under cloudy and overcast conditions, the heading angle error is reduced to less than 2°.

The interplay of directional information provided by unpolarised and polarised light in the heading direction network of the diurnal dung beetle Kheper lamarcki

The sun is the most prominent source of directional information in the heading direction network of the diurnal, ball-rolling dung beetle Kheper lamarcki. If this celestial body is occluded from the beetle's field of view, the distribution of the relative weight between the directional cues that remain shifts in favour of the celestial pattern of polarised light. In this study, we continue to explore the interplay of the sun and polarisation pattern as directional cues in the heading direction network of K. lamarcki. By systematically altering the intensity and degree of the two cues presented, we effectively change the relative reliability of these directional cues as they appear to the dung beetle. The response of the ball-rolling beetle to these modifications allows us to closely examine how the weighting relationship of these two sources of directional information is influenced and altered in the heading direction network of the beetle. We conclude that the process in which K. lamarcki relies on directional information is very likely done based on Bayesian reasoning, where directional information conveying the highest certainty at a particular moment is afforded the greatest weight.

Ultraviolet vision aids the detection of nutrient-dense non-signaling plant foods

To expand our understanding of what tasks are particularly helped by UV vision and may justify the costs of focusing high-energy light onto the retina, we used an avian-vision multispectral camera to image diverse vegetated habitats in search of UV contrasts that differ markedly from visible-light contrasts. One UV contrast that stood out as very different from visible-light contrasts was that of nutrient-dense non-signaling plant foods (such as young leaves and immature fruits) against their natural backgrounds. From our images, we calculated color contrasts between 62+ species of such foods and mature foliage for the two predominant color vision systems of birds, UVS and VS. We also computationally generated images of what a generalized tetrachromat, unfiltered by oil droplets, would see, by developing a new methodology that uses constrained linear least squares to solve for optimal weighted combinations of avian camera filters to mimic new spectral sensitivities. In all visual systems, we found that nutrient-dense non-signaling plant foods presented a lower, often negative figure-ground contrast in the UV channels, and a higher, often positive figure-ground contrast in the visible channels. Although a zero contrast may sound unhelpful, it can actually enhance color contrast when compared in a color opponent system to other channels with nonzero contrasts. Here, low or negative UV contrasts markedly enhanced color contrasts. We propose that plants may struggle to evolve better UV crypsis since UV reflectance from vegetation is largely specular and thus highly dependent on object orientation, shape, and texture.

Design and calibration model of a bioinspired attitude and heading reference system based on compound eye polarization compass

Insects such as honeybees are capable of fusing the information sensed by multiple sensory organs for attitude and heading determination. In this paper, inspired by the sensory fusion mechanism of insects' polarization compass and haltere, a bioinspired polarization-based attitude and heading reference system (PAHRS) is presented. The PAHRS consists of compound eye polarization compass and inertial measurement unit (IMU). By simulating multi-view structure of the dorsal rim area in insects' compound eyes, a non-coplanar 'polarization-opponent (POL)-type' architecture is adopted for the compound eye polarization compass. The polarization compass has multi-directional observation channels, which is capable of adaptively selecting the angle of polarization and obtaining the polarization vectors. Therefore, the environmental adaptability of the polarization compass can be enhanced. In addition, the integration strategy between the compound eye polarization compass and IMU is proposed. Moreover, the sources of system errors are analyzed to improve the heading angle accuracy, based on which a new calibration model is established to compensate the installation errors of the PAHRS. Finally, experiments are carried out under both clear sky and cloudy conditions. The test results show that the error root mean square of heading angle is 0.14° in clear sky, and 0.42° in partly cloudy conditions.

Limitation of Rayleigh sky model for bioinspired polarized skylight navigation in three-dimensional attitude determination

Insects such as desert ants and drosophilae can sense polarized skylight for navigation. Inspired by insects, many researchers have begun to study how to use skylight polarization patterns for attitude determination. The Rayleigh sky model has become the most widely used skylight polarization model for bioinspired polarized skylight navigation due to its simplicity and practicality. However, this is an ideal model considering only single Rayleigh scatter events, and the limitation of this model in bio-inspired attitude determination has not been paid much attention and lacks strict inference proof. To address this problem, the rotational and plane symmetry of the Rayleigh sky model are analyzed in detail, and it is theoretically proved that this model contains only single solar vector information, which contains only two independent scalar pieces of attitude information, so it is impossible to determine three Euler angles simultaneously in real-time. To further verify this conclusion, based on a designed hypothetical polarization camera, we discuss what conditions different three-dimensional attitudes must satisfy so that the polarization images taken at different 3D attitudes are the same; this indicates that multiple solutions will appear when only using the Rayleigh sky model to determine 3D attitude. In conclusion, due to its single solar vector information and the existence of multiple solutions, it is fully proved that 3D attitude cannot be determined in real time based only upon the Rayleigh sky model. Code is available at: https://github.com/HuajuLiang/HypotheticalPolarizationCamera.

Polarized skylight compass based on a soft-margin support vector machine working in cloudy conditions

The skylight polarization pattern, which is a result of the scattering of unpolarized sunlight by particles in the atmosphere, can be used by many insects for navigation. Inspired by insects, several polarization navigation sensors have been designed and combined with various heading determination methods in recent years. However, up until now, few of these studies have fully considered the influences of different meteorological conditions, which play key roles in navigation accuracy, especially in cloudy weather. Therefore, this study makes a major contribution to the study on bio-inspired heading determination by designing a skylight compass method to suppress cloud disturbances. The proposed method transforms the heading determination problem into a binary classification problem by segmentation, connected component detection, and inversion. Considering the influences of noise and meteorological conditions, the binary classification problem is solved by the soft-margin support vector machine. In addition, to verify this method, a pixelated polarization compass platform is constructed that can take polarization images at four different orientations simultaneously in real time. Finally, field experimental results show that the designed method can more effectively suppress the interference of clouds compared with other methods.