A Bio-Inspired Polarization Sensor with High Outdoor Accuracy and Central-Symmetry Calibration Method with Integrating Sphere

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.

Measurement Modeling and Performance Analysis of a Bionic Polarimetric Imaging Navigation Sensor Using Rayleigh Scattering to Generate Scattered Sunlight

The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement performance analysis method of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the overall measurement performance of BPINS are investigated, and the Stokes vector-based measurement error model of BPINS is introduced. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed using Rayleigh scattering to generate scattered sunlight as a known incident light source. The numerical results show that in angle of E-vector (AoE) measurement, the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation; in degree of linear polarization (DoLP) measurement, the grayscale response inconsistency of CMOS has a more significant impact. This finding can accurately guide the subsequent calibration of BPINS, and the quantitative results provide an important theoretical reference for its optimal design.

Design of a real-time orientation sensor based on atmospheric polarization light

In recent years, biomimetic polarization navigation has become a research hotspot in navigation fields because of its autonomy and concealment. Existing point-source polarization navigation sensors mainly use a logarithmic amplifier as the arithmetic unit to obtain polarization information. However, these sensors suffer from zero drift and low detection accuracy, which limits their application range. To address the above issues, a polarization navigation sensor based on a differential amplifier is designed as the operational unit. Based on the change of the arithmetic unit of the polarization signal, the algorithm for calculating the heading angle of the sensor is improved. The results of the orientation experiments with the designed sensor in clear weather indicate that the orientation error is ±1.243∘, and the standard deviation is 0.351°. The polarization navigation sensor can extract polarized light information and calculate the heading without accumulation of errors over time accurately and achieves good real-time performance.

Self-calibration algorithm for installation angle deviation of bionic polarization compound eyes

A self-calibration algorithm based on unsupervised optimization for polarizer installation angle deviation is proposed and used in a multi-aperture bionic polarization compound eye system. To simplify calibration operation, under the condition that the calibration-polarized light information is unknown, this algorithm fully exploits redundancy and random polarization information in the scene, and uses a non-convex multi-objective discrete parameter sorting optimization method to achieve angle self-calibration. Compared with ordinary calibration procedures, the algorithm requires less stringent conditions, achieves online calibration and is more accurate. It also can be applied to camera polarization arrays, division-of-focal-plane polarization cameras, and other polarization devices.

Biomimetic Polarized Light Navigation Sensor: A Review

A polarized light sensor is applied to the front-end detection of a biomimetic polarized light navigation system, which is an important part of analyzing the atmospheric polarization mode and realizing biomimetic polarized light navigation, having received extensive attention in recent years. In this paper, biomimetic polarized light navigation in nature, the mechanism of polarized light navigation, point source sensor, imaging sensor, and a sensor based on micro nano machining technology are compared and analyzed, which provides a basis for the optimal selection of different polarized light sensors. The comparison results show that the point source sensor can be divided into basic point source sensor with simple structure and a point source sensor applied to integrated navigation. The imaging sensor can be divided into a simple time-sharing imaging sensor, a real-time amplitude splitting sensor that can detect images of multi-directional polarization angles, a real-time aperture splitting sensor that uses a light field camera, and a real-time focal plane light splitting sensor with high integration. In recent years, with the development of micro and nano machining technology, polarized light sensors are developing towards miniaturization and integration. In view of this, this paper also summarizes the latest progress of polarized light sensors based on micro and nano machining technology. Finally, this paper summarizes the possible future prospects and current challenges of polarized light sensor design, providing a reference for the feasibility selection of different polarized light sensors.

A bio-inspired polarization navigation sensor based on artificial compound eyes

Insect compound eyes are optical systems with small volume and a compact structure. The ommatidia in the dorsal rim area of some insects have polarized vision, which can perceive the polarization pattern of the sky and provide them with navigation information. In this paper, inspired by the polarization-sensitive compound eyes of insects, a bio-inspired polarization navigation sensor based on artificial compound eyes is designed. The sensor consists of an artificial compound eye, an integrated polarization detector and an integrated circuit. The optical path of the sensor uses the lens defocus method, which can ensure that the sensor obtains redundant polarization information. The integrated polarization detector is used to obtain the polarization information of the incident light, and the integrated circuit is responsible for the calculation. To extract effective information from images, we propose a multi-threshold segmentation method to filter and classify effective pixels. We use the least squares method to fit the inherent error of the sensor and then compensate it. The indoor calibration accuracy of the sensor is ±0.3°, and the outdoor calibration accuracy is ±0.5°. The sensor can provide accurate direction information for general smart mobile devices. The size of the sensor is 4 × 4 × 2 cm, and the weight is only 15 g. The key components of the sensor can be mass-produced, and it is a miniaturized and low-cost polarization navigation sensor.

Biomimetic navigation system using a polarization sensor and a binocular camera

With the vigorous development of vision techniques, simultaneous localization and mapping (SLAM) has shown the capability of navigating autonomous robots in global-navigation-satellite-system-denied environments. However, the long-term robust navigation of lightweight autonomous robots in outdoor environments with complex interferences, such as illumination change, dynamic objects, and electromagnetic interference, is still a great challenge. In this paper, a polarization sensor-aided SLAM (POL-SLAM) that can provide absolute heading constraints for pure SLAM is proposed. POL-SLAM is a lightweight, tightly coupled system consisting of a polarization sensor and binocular camera. By means of an initialization that uses a polarization sensor, an absolute heading angle for the entire map is designed. Additionally, an algorithm to eliminate mismatching points using the matching point vector is proposed. The objective function of bundle adjustment is then deduced according to the re-projection error and polarization sensor. The vehicle test shows that the yaw and trajectory accuracies of POL-SLAM are significantly improved compared to pure SLAM. The yaw and trajectory accuracies are increased by 43.1% and 36.6%, respectively. These results indicate that the proposed POL-SLAM can improve the reliability and robustness of pure SLAM and can be used in lightweight autonomous robots in outdoor environments.

Measurement error model of the bio-inspired polarization imaging orientation sensor

This article studies the measurement error model and calibration method of the bio-inspired polarization imaging orientation sensor (BPIOS), which has important engineering significance for promoting bio-inspired polarization navigation. Firstly, we systematically analyzed the measurement errors in the imaging process of polarized skylight and accurately established an error model of BPIOS based on Stokes vector. Secondly, using the simulated Rayleigh skylight as the incident surface light source, the influence of multi-source factors on the measurement accuracy of BPIOS is quantitatively given for the first time. These simulation results can guide the later calibration of BPIOS. We then proposed a calibration method of BPIOS based on geometric parameters and the Mueller matrix of the optical system and conducted an indoor calibration experiment. Experimental results show that the measurement accuracy of the calibrated BPIOS can reach 0.136°. Finally, the outdoor performance of BPIOS is studied. Outdoor dynamic performance test and field compensation were performed. Outdoor results show that the heading accuracy of BPIOS is 0.667°.

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.

Sensor Modeling and Calibration Method Based on Extinction Ratio Error for Camera-Based Polarization Navigation Sensor

The performance of camera-based polarization sensors largely depends on the estimated model parameters obtained through calibration. Limited by manufacturing processes, the low extinction ratio and inconsistency of the polarizer can reduce the measurement accuracy of the sensor. To account for the challenges, one extinction ratio coefficient was introduced into the calibration model to unify the light intensity of two orthogonal channels. Since the introduced extinction ratio coefficient is associated with degree of polarization (DOP), a new calibration method considering both azimuth of polarization (AOP) error and DOP error for the bionic camera-based polarization sensor was proposed to improve the accuracy of the calibration model parameter estimation. To evaluate the performance of the proposed camera-based polarization calibration model using the new calibration method, both indoor and outdoor calibration experiments were carried out. It was found that the new calibration method for the proposed calibration model could achieve desirable performance in terms of stability and robustness of the calculated AOP and DOP values.

Bio-inspired attitude measurement method using a polarization skylight and a gravitational field

High precision and reliability attitude measurement play an important role in autonomous unmanned navigation. Finding inspiration from desert ants, known as highly efficient navigators who can find their way after foraging for hundreds of meters from their home in hostile environments, we propose an attitude measurement method using polarization skylight and gravitational field. Contrary to the previous method, we utilize three-dimensional polarization vectors and any one-dimensional output of the accelerometers to calculate attitudes. In addition, we designed an accelerometer component selection algorithm, which is to select the one-dimensional component with the minimum motion acceleration from the output of the three-dimensional accelerometer. With this method, even if the carriers remain in a maneuvering state, the motion acceleration of the vehicle will have less impact on the accuracy of attitude measurement. To evaluate the performance of our method, the outdoor experiment was carried out to compare our method with existing traditional methods. Comparison results show that our method has higher measurement accuracy than others and is still applicable in the case of carriers maneuvering in practice under a clear sky.