Autonomous outdoor navigation requires reliable multisensory fusion strategies. Desert ants travel widely every day, showing unrivaled navigation performance using only a few thousand neurons. In the desert, pheromones are instantly destroyed by the extreme heat. To navigate safely in this hostile environment, desert ants assess their heading from the polarized pattern of skylight and judge the distance traveled based on both a stride-counting method and the optic flow, i.e., the rate at which the ground moves across the eye. This process is called path integration (PI). Although many methods of endowing mobile robots with outdoor localization have been developed recently, most of them are still prone to considerable drift and uncertainty. We tested several ant-inspired solutions to outdoor homing navigation problems on a legged robot using two optical sensors equipped with just 14 pixels, two of which were dedicated to an insect-inspired compass sensitive to ultraviolet light. When combined with two rotating polarized filters, this compass was equivalent to two costly arrays composed of 374 photosensors, each of which was tuned to a specific polarization angle. The other 12 pixels were dedicated to optic flow measurements. Results show that our ant-inspired methods of navigation give precise performances. The mean homing error recorded during the overall trajectory was as small as 0.67% under lighting conditions similar to those encountered by ants. These findings show that ant-inspired PI strategies can be used to complement classical techniques with a high level of robustness and efficiency.

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AntBot: A six-legged walking robot able to home like desert ants in outdoor environments.

Animal senses cover a broad range of signal types and signal bandwidths and have inspired various sensors and bioinstrumentation devices for biological and medical applications. Insects, such as desert ants and honeybees, for example, utilize polarized skylight pattern-based information in their navigation activities. They reliably return to their nests and hives from places many kilometers away. The insect navigation system involves the dorsal rim area in their compound eyes and the corresponding polarization sensitive neurons in the brain. The dorsal rim area is equipped with photoreceptors, which have orthogonally arranged small hair-like structures termed microvilli. These are the specialized sensors for the detection of polarized skylight patterns (e-vector orientation). Various research groups have been working on the development of novel navigation systems inspired by polarized skylight-based navigation in animals. Their major contributions are critically reviewed. One focus of current research activities is on imitating the integration path mechanism in desert ants. The potential for simple, high performance miniaturized bioinstrumentation that can assist people in navigation will be explored.

/pdf/bio-inspired-polarized-skylight-based-navigation-sensors-a-5dvjmrz1ys.pdf

Bio-Inspired Polarized Skylight-Based Navigation Sensors: A Review

This paper aims to develop a novel attitude determination system aided by polarization sensor. An improved heading angle function is derived using the perpendicular relationship between directions of E-vector of linearly polarized light and solar vector in the atmospheric polarization distribution model. The Extended Kalman filter (EKF) with quaternion differential equation as a dynamic model is applied to fuse the data from sensors. The covariance functions of filter process and measurement noises are deduced in detail. The indoor and outdoor tests are conducted to verify the validity and feasibility of proposed attitude determination system. The test results showed that polarization sensor is not affected by magnetic field, thus the proposed system can work properly in environments containing the magnetic interference. The results also showed that proposed system has higher measurement accuracy than common attitude determination system and can provide precise parameters for Unmanned Aerial Vehicle (UAV) flight control. The main contribution of this paper is implementation of the EKF for incorporating the self-developed polarization sensor into the conventional attitude determination system. The real-world experiment with the quad-rotor proved that proposed system can work in a magnetic interference environment and provide sufficient accuracy in attitude determination for autonomous navigation of vehicle.

https://www.mdpi.com/1424-8220/18/1/158/pdf

A Novel Attitude Determination System Aided by Polarization Sensor.

Polarization is one of the three fundamental properties of light, along with color and intensity, yet most vertebrate species, including humans, are blind with respect to this light modality. In contrast, many invertebrates, including insects, spiders, cephalopods, and stomatopods, have evolved to detect polarization information with high-dynamic-range photosensitive cells and utilize this information in visually guided behavior. In this paper, we present a high-dynamic-range polarization imaging sensor inspired by the visual system of the mantis shrimp. Our bioinspired imager achieves 140 dB dynamic range and 61 dB maximum signal-to-noise ratio across 384×288 pixels equipped with logarithmic photodiodes. Contrary to state-of-the-art active pixel sensors, where photodiodes in individual pixels operate in reverse bias mode and yield up to ∼60  dB dynamic range, our pixel has a logarithmic response by operating individual photodiodes in forward bias mode. This novel pixel circuitry is monolithically integrated with pixelated polarization filters composed of 250-nm-tall × 75-nm-wide aluminum nanowires to enable snapshot polarization imaging at 30 frames per second. This sensor can enable many automotive and remote sensing applications, where high-dynamic-range imaging augmented with polarization information can provide critical information during hazy or rainy conditions.

Bioinspired polarization imager with high dynamic range

An ant-inspired celestial compass applied to autonomous outdoor robot navigation

Orientation and position information are indispensable in mobile robot navigation. In this paper, a novel polarization sensor for getting orientation information is introduced. It exports an absolute azimuth angle. To take it effect in mobile robot navigation, a fuzzy logic controller is designed. It can direct the robot walking along the designed trajectory according to the information from the polarization sensor. Assisted by the wheel encoders, some navigation experiments are implemented outdoors. The result indicates that the error of the polarization sensor is independent of the travel distance and it can play an important role in automatic navigation system in a further way.

Application of a novel polarization sensor to mobile robot navigation

Inspired by human behaviors, a robot object tracking model is proposed on the basis of visual attention mechanism, which is fit for the theory of topological perception. The model integrates the image-driven, bottom-up attention and the object-driven, top-down attention, whereas the previous attention model has mostly focused on either the bottom-up or top-down attention. By the bottom-up component, the whole scene is segmented into the ground region and the salient regions. Guided by top-down strategy which is achieved by a topological graph, the object regions are separated from the salient regions. The salient regions except the object regions are the barrier regions. In order to estimate the model, a mobile robot platform is developed, on which some experiments are implemented. The experimental results indicate that processing an image with a resolution of 752 × 480 pixels takes less than 200ms and the object regions are unabridged. The analysis obtained by comparing the proposed model with the existing model demonstrates that the proposed model has some advantages in robot object tracking in terms of speed and efficiency.

A visual attention model for robot object tracking

The invention discloses a human eye and human neck simulating vision device, which relates to a vision system platform. The pitching and flat-turning motions of the human eye and the human neck are flexible and harmonious, and the vision device has the functions of acquiring and transmitting images. The vision device consists of a human eye simulating mechanism, a left turntable component, a right turntable component, a slide rail component and a human neck simulating mechanism. The human eye simulating mechanism consists of left and right camera assemblies which are fully symmetrical. The human neck simulating mechanism consists of a pitching transmission mechanism and a flat-turning transmission mechanism, wherein the pitching transmission mechanism is implemented through the transmission of a pitching motor and a pitching worm or worm gear inside the human neck simulating mechanism, and the flat-turning transmission mechanism is implemented through the transmission of a flat-turning motor and a flat-turning worm or worm gear inside the human neck simulating mechanism. A slide rail cross beam in the slide rail component is a slide rail with scales and two dovetail grooves. The vision device has the advantages of strong environment adaptability due to the adoption of an independent power supply, high motion precision, stability, low noise, simple mechanism, reliable performance and low power.

Hongqing Wang

Papers

Application of a novel polarization sensor to mobile robot navigation

A visual attention model for robot object tracking

Human eye and human neck simulating vision device

Swin-T-NFC CRFs: An encoder-decoder neural model for high-precision UAV positioning via point cloud super resolution and image semantic segmentation