A novel autonomous real-time position method based on polarized light and geomagnetic field

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.

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 3D Attitude Estimation Method Based on Attitude Angular Partial Feedback for Polarization-Based Integrated Navigation System

Polarization (POL) navigation is inspired by insects’ behavior of precepting celestial polarization patterns to orient themselves. It has the advantages of being autonomous and having no accumulative error, which allows it to be used to correct the errors of the inertial navigation system (INS). The integrated navigation system of the POL-based solar vector with INS is capable of 3D attitude determination. However, the commonly used POL-based integrated navigation system generally implements the attitude update procedure without considering the performance difference with different magnitudes of the angles between the solar-vector and body-axes of the platform (S-B angles). When one of the S-B angles is small enough, the estimated accuracy of the attitude angle by the INS/POL is worse than that of the strapdown inertial navigation system. To minimize the negative impact of POL in this situation, an attitude angular adaptive partial feedback method is proposed. The S-B angles are used to construct a partial feedback factor matrix to adaptively adjust the degree of error correction for INS. The results of simulation and real-world experiments demonstrate that the proposed method can improve the accuracy of 3D attitude estimation compared with the conventional all-feedback method for small S-B angles especially for yaw angle estimation.

Advances in Smart Sensing and Medical Electronics by Self-Powered Sensors Based on Triboelectric Nanogenerators

With the rapid progress of artificial intelligence, humans are moving toward the era of the intelligent connection of all things. Therefore, the demand for sensors is drastically increasing with developing intelligent social applications. Traditional sensors must be triggered by an external power source and the energy consumption is high for equipment that is widely distributed and working intermittently, which is not conducive to developing sustainable green and healthy applications. However, self-powered sensors based on triboelectric nanogenerators (TENG) can autonomously harvest energy from the surrounding environment and convert this energy into electrical energy for storage. Sensors can also be self-powered without an external power supply, which is vital for smart cities, smart homes, smart transportation, environmental monitoring, wearable devices, and bio-medicine. This review mainly summarizes the working mechanism of TENG and the research progress of self-powered sensors based on TENG about the Internet of Things (IoT), robotics, human–computer interaction, and intelligent medical fields in recent years.

The Triboelectric Nanogenerator as an Innovative Technology toward Intelligent Sports

In the new era of the Internet-of-Things, athletic big data collection and analysis based on widely distributed sensing networks are particularly important in the development of intelligent sports. Conventional sensors usually require an external power supply, with limitations such as limited lifetime and high maintenance cost. As a newly developed mechanical energy harvesting and self-powered sensing technology, the triboelectric nanogenerator (TENG) shows great potential to overcome these limitations. Most importantly, TENGs can be fabricated using wood, paper, fibers, and polymers, which are the most frequently used materials for sports. Recent progress on the development of TENGs for the field of intelligent sports is summarized. First, the working mechanism of TENG and its association with athletic big data are introduced. Subsequently, the development of TENG-based sports sensing systems, including smart sports facilities and wearable equipment is highlighted. At last, the remaining challenges and open opportunities are also discussed.

Bionic Integrated Positioning Mechanism Based on Bioinspired Polarization Compass and Inertial Navigation System

In this paper, to address the problem of positioning accumulative errors of the inertial navigation system (INS), a bionic autonomous positioning mechanism integrating INS with a bioinspired polarization compass is proposed. In addition, the bioinspired positioning system hardware and the integration model are also presented. Concerned with the technical issue of the accuracy and environmental adaptability of the integrated positioning system, the sun elevation calculating method based on the degree of polarization (DoP) and direction of polarization (E-vector) is presented. Moreover, to compensate for the latitude and longitude errors of INS, the bioinspired positioning system model combining the polarization compass and INS is established. Finally, the positioning performance of the proposed bioinspired positioning system model was validated via outdoor experiments. The results indicate that the proposed system can compensate for the position errors of INS with satisfactory performance.

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.

Formation experiment with heading angle reference using sky polarization pattern at twilight

Consistency has always been an important topic in formation cooperation research. Traditional navigation methods, such as inertial navigation and geomagnetic navigation, have the disadvantages of error accumulation and low stability, thus reducing the consistency of formation. We propose to use the skylight polarization pattern to provide heading angle reference for formation cooperation of multi-agents. The experimental results show that the polarization navigation has good stability and no error accumulation. First, we analyzed the consistency of using the skylight polarization pattern to provide a heading reference for formation experiments. Then, based on the bionic polarization navigation sensor, we measured the difference of the skylight polarization azimuth of different observers at twilight. Further, a mobile robot platform was built with its heading angle provided by a polarization navigation sensor. Finally, we present an overview of a 3-robots platform formation experiment at twilight.

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

A bio-inspired polarization sensor with lenses for navigation was evaluated in this study. Two new calibration methods are introduced, referred to as "central-symmetry calibration" (with an integrating sphere) and "noncontinuous calibration". A comparison between the indoor calibration results obtained from different calibration methods shows that the two proposed calibration methods are more effective. The central-symmetry calibration method optimized the nonconstant calibration voltage deviations, caused by the off-axis feature of the integrating sphere, to be constant values which can be calibrated easily. The section algorithm proposed previously showed no experimental advantages until the central-symmetry calibration method was proposed. The outdoor experimental results indicated that the indoor calibration parameters did not perform very well in practice outdoor conditions. To establish the reason, four types of calibration parameters were analyzed using the replacement method. It can be concluded that three types can be easily calibrated or affect the sensor accuracy slightly. However, before the sensor is used outdoors every time, the last type must be replaced with the corresponding outdoor parameter, and the calculation needs a precise rotary table. This parameter, which is mainly affected by the spectrum of incident light, is the main factor determining the sensor accuracy. After calibration, the sensor reaches an indoor accuracy of ±0.009° and a static outdoor accuracy of ±0.05° under clear sky conditions. The dynamic outdoor experiment shows a ±0.5° heading deviation between the polarization sensor and the inertial navigation system with a ±0.06° angular accuracy.

Polarized skylight-based heading measurements: a bio-inspired approach

Many insects such as desert ants, crickets, locusts, dung beetles, bees and monarch butterflies have been found to extract their navigation cues from the regular pattern of the linearly polarized skylight. These species are equipped with ommatidia in the dorsal rim area of their compound eyes, which are sensitive to the angle of polarization of the skylight. In the polarization-based robotic vision, most of the sensors used so far comprise high-definition CCD or CMOS cameras topped with linear polarizers. Here, we present a 2-pixel polarization-sensitive visual sensor, which was strongly inspired by the dorsal rim area of desert ants' compound eyes, designed to determine the direction of polarization of the skylight. The spectral sensitivity of this minimalistic sensor, which requires no lenses, is in the ultraviolet range. Five different methods of computing the direction of polarization were implemented and tested here. Our own methods, the extended and AntBot method, outperformed the other three, giving a mean angular error of only 0.62° ± 0.40° (median: 0.24°) and 0.69° ± 0.52° (median: 0.39°), respectively (mean ± standard deviation). The results obtained in outdoor field studies show that our celestial compass gives excellent results at a very low computational cost, which makes it highly suitable for autonomous outdoor navigation purposes.

Insect-inspired vision for autonomous vehicles

Flying insects are being studied these days as if they were agile micro air vehicles fitted with smart sensors, requiring very few brain resources. The findings obtained on these natural fliers have proved to be extremely valuable when it comes to designing compact low-weight artificial optical sensors capable of performing visual processing tasks robustly under various environmental conditions (light, clouds, contrast). Here, we review some outstanding bio-inspired visual sensors, which can be used for either detecting motion in the visible spectrum or controlling celestial navigation in the ultraviolet spectrum and for attitude stabilisation purposes. Biologically inspired visual sensors do not have to comprise a very large number of pixels: they are able to perform both short and long range navigation tasks surprisingly well with just a few pixels and a weak resolution.

Global positioning method based on polarized light compass system

This paper presents a global positioning method based on a polarized light compass system. A main limitation of polarization positioning is the environment such as weak and locally destroyed polarization environments, and the solution to the positioning problem is given in this paper which is polarization image de-noising and segmentation. Therefore, the pulse coupled neural network is employed for enhancing positioning performance. The prominent advantages of the present positioning technique are as follows: (i) compared to the existing position method based on polarized light, better sun tracking accuracy can be achieved and (ii) the robustness and accuracy of positioning under weak and locally destroyed polarization environments, such as cloudy or building shielding, are improved significantly. Finally, some field experiments are given to demonstrate the effectiveness and applicability of the proposed global positioning technique. The experiments have shown that our proposed method outperforms the conventional polarization positioning method, the real time longitude and latitude with accuracy up to 0.0461° and 0.0911°, respectively.

Orthogonal vector algorithm to obtain the solar vector using the single-scattering Rayleigh model

Information obtained from a polarization pattern in the sky provides many animals like insects and birds with vital long-distance navigation cues. The solar vector can be derived from the polarization pattern using the single-scattering Rayleigh model. In this paper, an orthogonal vector algorithm, which utilizes the redundancy of the single-scattering Rayleigh model, is proposed. We use the intersection angles between the polarization vectors as the main criteria in our algorithm. The assumption that all polarization vectors can be considered coplanar is used to simplify the three-dimensional (3D) problem with respect to the polarization vectors in our simulation. The surface-normal vector of the plane, which is determined by the polarization vectors after translation, represents the solar vector. Unfortunately, the two-directionality of the polarization vectors makes the resulting solar vector ambiguous. One important result of this study is, however, that this apparent disadvantage has no effect on the complexity of the algorithm. Furthermore, two other universal least-squares algorithms were investigated and compared. A device was then constructed, which consists of five polarized-light sensors as well as a 3D attitude sensor. Both the simulation and experimental data indicate that the orthogonal vector algorithms, if used with a suitable threshold, perform equally well or better than the other two algorithms. Our experimental data reveal that if the intersection angles between the polarization vectors are close to 90°, the solar-vector angle deviations are small. The data also support the assumption of coplanarity. During the 51 min experiment, the mean of the measured solar-vector angle deviations was about 0.242°, as predicted by our theoretical model.

Novel robust skylight compass method based on full-sky polarization imaging under harsh conditions

A novel method based on Pulse Coupled Neural Network(PCNN) algorithm for the highly accurate and robust compass information calculation from the polarized skylight imaging is proposed,which showed good accuracy and reliability especially under cloudy weather,surrounding shielding and moon light. The degree of polarization (DOP) combined with the angle of polarization (AOP), calculated from the full sky polarization image, were used for the compass information caculation. Due to the high sensitivity to the environments, DOP was used to judge the destruction of polarized information using the PCNN algorithm. Only areas with high accuracy of AOP were kept after the DOP PCNN filtering, thereby greatly increasing the compass accuracy and robustness. From the experimental results, it was shown that the compass accuracy was 0.1805° under clear weather. This method was also proven to be applicable under conditions of shielding by clouds, trees and buildings, with a compass accuracy better than 1°. With weak polarization information sources, such as moonlight, this method was shown experimentally to have an accuracy of 0.878°.

Robust sky light polarization detection with an S-wave plate in a light field camera

The sky light polarization navigator has many advantages, such as low cost, no decrease in accuracy with continuous operation, etc. However, current celestial polarization measurement methods often suffer from low performance when the sky is covered by clouds, which reduce the accuracy of navigation. In this paper we introduce a new method and structure based on a handheld light field camera and a radial polarizer, composed of an S-wave plate and a linear polarizer, to detect the sky light polarization pattern across a wide field of view in a single snapshot. Each micro-subimage has a special intensity distribution. After extracting the texture feature of these subimages, stable distribution information of the angle of polarization under a cloudy sky can be obtained. Our experimental results match well with the predicted properties of the theory. Because the polarization pattern is obtained through image processing, rather than traditional methods based on mathematical computation, this method is less sensitive to errors of pixel gray value and thus has better anti-interference performance.

Sky light polarization detection with linear polarizer triplet in light field camera inspired by insect vision

Stable information of a sky light polarization pattern can be used for navigation with various advantages such as better performance of anti-interference, no "error cumulative effect," and so on. But the existing method of sky light polarization measurement is weak in real-time performance or with a complex system. Inspired by the navigational capability of a Cataglyphis with its compound eyes, we introduce a new approach to acquire the all-sky image under different polarization directions with one camera and without a rotating polarizer, so as to detect the polarization pattern across the full sky in a single snapshot. Our system is based on a handheld light field camera with a wide-angle lens and a triplet linear polarizer placed over its aperture stop. Experimental results agree with the theoretical predictions. Not only real-time detection but simple and costless architecture demonstrates the superiority of the approach proposed in this paper.