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Serres JR, Lapray PJ, Viollet S, Kronland-Martinet T, Moutenet A, Morel O, Bigué L. Passive Polarized Vision for Autonomous Vehicles: A Review. SENSORS (BASEL, SWITZERLAND) 2024; 24:3312. [PMID: 38894104 PMCID: PMC11174665 DOI: 10.3390/s24113312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/10/2024] [Accepted: 05/14/2024] [Indexed: 06/21/2024]
Abstract
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.
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Affiliation(s)
- Julien R. Serres
- The Institute of Movement Sciences, Aix Marseille University, CNRS, ISM, CEDEX 09, 13284 Marseille, France; (S.V.); (T.K.-M.); (A.M.)
- Institut Universitaire de France (IUF), 1 Rue Descartes, CEDEX 05, 75231 Paris, France
| | - Pierre-Jean Lapray
- The Institute for Research in Computer Science, Mathematics, Automation and Signal, Université de Haute-Alsace, IRIMAS UR 7499, 68100 Mulhouse, France;
| | - Stéphane Viollet
- The Institute of Movement Sciences, Aix Marseille University, CNRS, ISM, CEDEX 09, 13284 Marseille, France; (S.V.); (T.K.-M.); (A.M.)
| | - Thomas Kronland-Martinet
- The Institute of Movement Sciences, Aix Marseille University, CNRS, ISM, CEDEX 09, 13284 Marseille, France; (S.V.); (T.K.-M.); (A.M.)
- Materials Microelectronics Nanosciences Institute of Provence, Aix Marseille University, Université de Toulon, CNRS, IM2NP, 13013 Marseille, France
| | - Antoine Moutenet
- The Institute of Movement Sciences, Aix Marseille University, CNRS, ISM, CEDEX 09, 13284 Marseille, France; (S.V.); (T.K.-M.); (A.M.)
- Safran Electronics & Defense, 100 Av. de Paris, 91344 Massy, France
| | - Olivier Morel
- ImViA, Laboratory, University of Bourgogne, 71200 Le Creusot, France;
| | - Laurent Bigué
- The Institute for Research in Computer Science, Mathematics, Automation and Signal, Université de Haute-Alsace, IRIMAS UR 7499, 68100 Mulhouse, France;
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Zhao H, Shen C, Cao H, Chen X, Wang C, Huang H, Li J. Seamless Micro-Electro-Mechanical System-Inertial Navigation System/Polarization Compass Navigation Method with Data and Model Dual-Driven Approach. MICROMACHINES 2024; 15:237. [PMID: 38398966 PMCID: PMC10892783 DOI: 10.3390/mi15020237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/25/2024]
Abstract
The integration of micro-electro-mechanical system-inertial navigation systems (MEMS-INSs) with other autonomous navigation sensors, such as polarization compasses (PCs) and geomagnetic compasses, has been widely used to improve the navigation accuracy and reliability of vehicles in Internet of Things (IoT) applications. However, a MEMS-INS/PC integrated navigation system suffers from cumulative errors and time-varying measurement noise covariance in unknown, complex occlusion, and dynamic environments. To overcome these problems and improve the integrated navigation system's performance, a dual data- and model-driven MEMS-INS/PC seamless navigation method is proposed. This system uses a nonlinear autoregressive neural network (NARX) based on the Gauss-Newton Bayesian regularization training algorithm to model the relationship between the MEMS-INS outputs composed of the specific force and angular velocity data and the PC heading's angular increment, and to fit the integrated navigation system's dynamic characteristics, thus realizing data-driven operation. In the model-driven part, a nonlinear MEMS-INS/PC loosely coupled navigation model is established, the variational Bayesian method is used to estimate the time-varying measurement noise covariance, and the cubature Kalman filter method is then used to solve the nonlinear problem in the model. The robustness and effectiveness of the proposed method are verified experimentally. The experimental results show that the proposed method can provide high-precision heading information stably in complex, occluded, and dynamic environments.
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Affiliation(s)
- Huijun Zhao
- The State Key Laboratory of Dynamic Measurement Technology, The School of Instrument and Electronics, North University of China, Taiyuan 030051, China
| | - Chong Shen
- The State Key Laboratory of Dynamic Measurement Technology, The School of Instrument and Electronics, North University of China, Taiyuan 030051, China
| | - Huiliang Cao
- The State Key Laboratory of Dynamic Measurement Technology, The School of Instrument and Electronics, North University of China, Taiyuan 030051, China
| | - Xuemei Chen
- The Intelligent Vehicle Research Center, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
| | - Chenguang Wang
- The State Key Laboratory of Dynamic Measurement Technology, The School of Instrument and Electronics, North University of China, Taiyuan 030051, China
| | - Haoqian Huang
- The College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
| | - Jie Li
- The State Key Laboratory of Dynamic Measurement Technology, The School of Instrument and Electronics, North University of China, Taiyuan 030051, China
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Dou Q, Du T, Wang Y, Liu X, Wang W. Optimal vector matching fusion method for bionic compound eye polarization compass and inertial sensor integration. ISA TRANSACTIONS 2023; 141:496-506. [PMID: 37479597 DOI: 10.1016/j.isatra.2023.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 04/10/2023] [Accepted: 07/07/2023] [Indexed: 07/23/2023]
Abstract
The compound eyes of insects can extract the heading by sensing multi-directional polarization information. Inspired by this, the integration with bionic eye polarization compass and low-precision MEMS inertial sensors yields a new choice for autonomous navigation in a GPS-denied environment. However, the occlusion environments, such as jungles and buildings, seriously affects the attitude estimation accuracy by destroying the polarization information. Considering the above problem, this paper proposes a reliable attitude estimation method based on vector matching measurement models for integration with bionic compound eye polarization compass and low-cost MEMS inertial sensors, including the polarization vector, solar vector, and gravity vector. To realize the matching and fusion among these vector models, the vector optimization selection algorithm is designed according to the number of visible polarization sensors in the occlusion environment. Particularly, the vector optimization selection factor is designed according to the error between the measured and theoretical polarization vectors. Furthermore, when using the solar vector estimation model, the degree of the polarization is applied to improve the calculation accuracy of the solar vector. The gravity vector measurement model is employed to enhance the autonomy of the integration. Finally, the effectiveness of the proposed method is verified by simulated and outdoor experiments under tree obscuration.
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Affiliation(s)
- Qingfeng Dou
- The School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
| | - Tao Du
- The School of Information Science and Technology, North China University of Technology, Beijing 100144, China.
| | - Yan Wang
- The School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
| | - Xin Liu
- The School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
| | - Wei Wang
- China Aerospace Science and Technology Corporation, Beijing 100048, China; Beijing Institute of Aerospace Control Devices, Beijing 100039, China
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Li S, Kong F, Xu H, Guo X, Li H, Ruan Y, Cao S, Guo Y. Biomimetic Polarized Light Navigation Sensor: A Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:5848. [PMID: 37447698 DOI: 10.3390/s23135848] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/15/2023] [Accepted: 06/17/2023] [Indexed: 07/15/2023]
Abstract
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.
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Affiliation(s)
- Shunzi Li
- College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China
| | - Fang Kong
- College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China
| | - Han Xu
- College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China
| | - Xiaohan Guo
- School of Information Science and Engineering, Shandong University, Qingdao 266237, China
| | - Haozhe Li
- College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China
| | - Yaohuang Ruan
- College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China
| | - Shouhu Cao
- College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China
| | - Yinjing Guo
- College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China
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Zhang J, Wang S, Li W, Qiu Z. A Multi-Mode Switching Variational Bayesian Adaptive Kalman Filter Algorithm for the SINS/PNS/GMNS Navigation System of Pelagic Ships. SENSORS 2022; 22:s22093372. [PMID: 35591062 PMCID: PMC9100650 DOI: 10.3390/s22093372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 04/20/2022] [Accepted: 04/23/2022] [Indexed: 12/10/2022]
Abstract
The ocean-going environment is complex and changeable with great uncertainty, which poses a huge challenge to the navigation ability of ships working in the pelagic ocean. In this paper, in an attempt to deal with the complex uncertain interference that the environment may bring to the strap-down inertial navigation system/polarization navigation system/geomagnetic navigation system (SINS/PNS/GMNS) integrated navigation system, the multi-mode switching variational Bayesian adaptive Kalman filter (MMS-VBAKF) algorithm is proposed. To be more specific, to identify the degrees of measurement interference more effectively, we design an interference evaluation and multi-mode switching mechanism using the original polarization information and geomagnetic information. Through this mechanism, the interference to the SINS/PNS/GMNS navigation system is divided into three cases. In case of slight interference (case SI), the variational Bayesian method is adopted directly to solve the problem that the statistical characteristics of measurement noise are unknown. By the fixed-point iteration mechanism, the statistical properties of the measurement noise and the system states can be estimated adaptively in real time. In case of interference-tolerance (case TI), the estimation of the statistical characteristics of measurement noise need to weigh the measurement information at the moment and a priori value information comprehensively. In case of excessive interference (case EI), the SINS/PNS/GMNS integrated navigation system will perform mode switching and filtering system reconstruction in advance. Then, the information fusion and navigation states estimation can be completed. Consequently, the reliability, robustness, and accuracy of the SINS/PNS/GMNS integrated navigation system can be guaranteed. Finally, the effectiveness of the algorithm is illustrated by the simulation experiments.
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Affiliation(s)
- Jie Zhang
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China;
| | - Shanpeng Wang
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China;
| | - Wenshuo Li
- Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, China
- Correspondence: (W.L.); (Z.Q.)
| | - Zhenbing Qiu
- Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, China
- Correspondence: (W.L.); (Z.Q.)
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A 3D Attitude Estimation Method Based on Attitude Angular Partial Feedback for Polarization-Based Integrated Navigation System. SENSORS 2022; 22:s22030710. [PMID: 35161457 PMCID: PMC8840561 DOI: 10.3390/s22030710] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 01/08/2022] [Accepted: 01/12/2022] [Indexed: 01/27/2023]
Abstract
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.
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Bessler S, Hess K, Weigt H, von Ramin M. Biological transformation-battery protection inspired by wound healing. BIOINSPIRATION & BIOMIMETICS 2021; 16:056008. [PMID: 34233318 DOI: 10.1088/1748-3190/ac1249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 07/07/2021] [Indexed: 06/13/2023]
Abstract
One of the major challenges for electric vehicle safety and mobility is the development of battery protection mechanisms that are able to cope with irregular and unpredictable heating of the battery unit. Biological protection mechanisms are considered to be one of the most effective and resilient mechanisms due to their ability to react dynamically and adaptively to unpredictable disturbances. Consequently, biological systems can be viewed as models for high resiliency that provide inspiration for tackling issues such as excessive resource consumption or low technical resilience. This study demonstrates the improvement of the safety of an electric vehicle battery system inspired by wound healing and pain reflex response, which are among the most important protective mechanisms of the human body system. In particular, the individual mechanisms are systematically characterized, their underlying principles identified and transferred to a simulated battery system using a novel attribute-based method. As a result, the detection of irregular heating is improved and cooling of the battery system is more efficient. Further, this example can be used to explain how protective mechanisms that contribute to the resilience of biological systems can be abstracted and transferred to different technical systems.
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Affiliation(s)
- Simon Bessler
- Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Am Klingelberg 1, 79588 Efringen-Kirchen, Germany
| | - Katharina Hess
- Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Am Klingelberg 1, 79588 Efringen-Kirchen, Germany
| | - Henning Weigt
- Fraunhofer Institute for Toxicology and Experimental Medicine, Nikolai-Fuchs-Straße 1, 30625 Hannover, Germany
| | - Malte von Ramin
- Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Am Klingelberg 1, 79588 Efringen-Kirchen, Germany
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Bionic Integrated Positioning Mechanism Based on Bioinspired Polarization Compass and Inertial Navigation System. SENSORS 2021; 21:s21041055. [PMID: 33557099 PMCID: PMC7913815 DOI: 10.3390/s21041055] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 11/16/2022]
Abstract
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.
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