Measuring solar vector with polarization sensors based on polarization pattern

Yang, Zhongguang; Zhou, Jun; Huang, He; Liu, Yingying; Li, Zhengkai

doi:10.1016/j.ijleo.2017.03.122

Cited by 10 publications

(12 citation statements)

References 22 publications

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“…Their approach also works in tilted environments by integrating inertial measurement unit (IMU) data. Finally, Yang et al [87] follow up Sahabot’s work, use 2 POL-OP units oriented in different angles from the zenith, placed on a plane and use the scanning technique in order to get values from different angles. They show that their sensor can estimate the solar azimuth and elevation in clear sky conditions with MAE 0.2° and 0.4° respectively.…”

Section: Discussionmentioning

confidence: 99%

From skylight input to behavioural output: A computational model of the insect polarised light compass

et al. 2019

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Many insects navigate by integrating the distances and directions travelled on an outward path, allowing direct return to the starting point. Fundamental to the reliability of this process is the use of a neural compass based on external celestial cues. Here we examine how such compass information could be reliably computed by the insect brain, given realistic constraints on the sky polarisation pattern and the insect eye sensor array. By processing the degree of polarisation in different directions for different parts of the sky, our model can directly estimate the solar azimuth and also infer the confidence of the estimate. We introduce a method to correct for tilting of the sensor array, as might be caused by travel over uneven terrain. We also show that the confidence can be used to approximate the change in sun position over time, allowing the compass to remain fixed with respect to ‘true north’ during long excursions. We demonstrate that the compass is robust to disturbances and can be effectively used as input to an existing neural model of insect path integration. We discuss the plausibility of our model to be mapped to known neural circuits, and to be implemented for robot navigation.

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Section: Discussionmentioning

confidence: 99%

From skylight input to behavioural output: A computational model of the insect polarised light compass

et al. 2019

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“…The algorithm can be summarized in Table 2: Equation (4) expressed the sun vector fused with the DoP and e-vector. Distinguished from [28], [30], the proposed method takes into account the influence of environmental factors on the sun vector calculation performance. By making full use of the polarized skylight information, the accuracy and robustness of the sun vector calculation can be consequently improved.…”

Section: B the Sun Vector Calculation Methods Based On Dop And E-vector Fusionmentioning

confidence: 99%

A Bio-Inspired Navigation Strategy Fused Polarized Skylight and Starlight for Unmanned Aerial Vehicles

et al. 2020

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The migratory animals are capable of traveling long distances by fusing varied information, such as the halteres, the star positions, and the polarization pattern. Motivated by the navigation strategy of migratory animals, a bio-inspired navigation strategy based on polarized skylight, starlight, and halteres is presented in this paper. To enhance the environmental adaptability of the polarization navigation system, a sun vector calculation method tightly fusing the degree of polarization (DoP) and the azimuth of polarization (e-vector) is proposed. By setting the threshold of DoP values of the observation points, the DoP and the e-vector within the threshold range can be selected to deduce the sun position. As such, the robustness and reliability of the sun position can be improved. Concerned with the issue of attitude and heading determination in GNSS-challenged conditions, an integrated navigation strategy combined with polarized light and starlight is proposed. In addition, a Kalman filter is adopted to fuse the navigation data of polarized light, starlight, and inertial sensors. Finally, simulations are conducted to validate the performance of the integrated model. The results illustrated that the proposed navigation strategy is capable of determining the attitude and heading in the scenarios of which the Global Navigation Satellite System (GNSS) is disturbed.

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“…Examples of the application of the polarised light compass for robot navigation are described in. [12][13][14][15][16] In principle, the sun and its associated pattern of polarised light can also be used to compute yaw rates. However, this system breaks down or performs poorly when the sun is directly or nearly overhead, because of the rotational symmetry of the pattern of intensity or polarisation of the skylight about the sun's axis.…”

Section: Biologically Inspired Approachesmentioning

confidence: 99%

Vision-only egomotion estimation in 6DOF using a sky compass

et al. 2018

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SUMMARYA novel pure-vision egomotion estimation algorithm is presented, with extensions to Unmanned Aerial Systems (UAS) navigation through visual odometry. Our proposed method computes egomotion in two stages using panoramic images segmented into sky and ground regions. Rotations (in 3DOF) are estimated by using a customised algorithm to measure the motion of the sky image, which is affected only by the rotation of the aircraft, and not by its translation. The rotation estimate is then used to derotate the optic flow field generated by the ground, from which the translation of the aircraft (in 3DOF) is estimated by another customised, iterative algorithm. Segmentation of the rotation and translation estimations allows for a partial relaxation of the planar ground assumption, inherently increasing the robustness of the approach. The translation vectors are scaled using stereo-based height to compute the current UAS position through path integration for closed-loop navigation. Outdoor field tests of our approach in a small quadrotor UAS suggest that the technique is comparable to the performance of existing state-of-the-art vision-based navigation algorithms, whilst also removing all dependence on additional sensors, such as an IMU or global positioning system (GPS).

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Measuring solar vector with polarization sensors based on polarization pattern

Cited by 10 publications

References 22 publications

From skylight input to behavioural output: A computational model of the insect polarised light compass

From skylight input to behavioural output: A computational model of the insect polarised light compass

A Bio-Inspired Navigation Strategy Fused Polarized Skylight and Starlight for Unmanned Aerial Vehicles

Vision-only egomotion estimation in 6DOF using a sky compass

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