Bio-Inspired Approach for Long-Range Underwater Navigation Using Model Predictive Control

Zhang, Yongding; Liu, Xiaofeng; Luo, Minzhou; Yang, Chenguang

doi:10.1109/tcyb.2019.2933397

Cited by 31 publications

(17 citation statements)

References 47 publications

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“…This article studies in the geomagnetic environment constructed by IGRF12, rather than measuring the real GF. As the basis of geomagnetic navigation, the uniqueness of the GF is discussed in [26].…”

Section:  mentioning

confidence: 99%

“…For the convenience of expression, the predicted heading angle is denoted as k  . The gradients are obtained by the simple decomposition of the changes of geomagnetism elements between two successive sampling locations in the east and north directions [26]. Thus, the heading angles at step 1 and step 2 are set as 0° and 90° respectively, and the geomagnetic gradient was calculated through the geomagnetic elements measured by magnetic sensors.…”

Section: Algorithmmentioning

confidence: 99%

“…The research works have confirmed the feasibility of the underwater geomagnetic navigation, but navigation strategy in geomagnetic anomaly areas and navigation trajectory need to be further optimized. A long-distance geomagnetic navigation method based on model predictive control was proposed in [26], which calculates the optimal control sequence according to magnetic declination and magnetic inclination. However, the actual magnetic anomaly areas are often more complex and cannot be treated as a constant.…”

Section: Introductionmentioning

confidence: 99%

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Geomagnetic Gradient-Assisted Evolutionary Algorithm for Long-Range Underwater Navigation

Zhang

Shin

et al. 2021

IEEE Trans. Instrum. Meas.

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Extensive research results have shown that animals like pigeons and turtles can use geomagnetic information for long-distance migration and homing. This article studies the bionic navigation method inspired by magnetotaxis behavior without prior knowledge. The problem of bionic geomagnetic navigation is generalized as an autonomous search of navigation path under the excitation of geomagnetic environment. The geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation is proposed. In order to optimize the navigation path, the heading angle predicted by the geomagnetic gradient is used to constrain the sample space in the evolutionary algorithm. Then, according to the principle of multi-parameter simultaneous convergence, the evaluation function is improved to enhance the reliability and accuracy of the navigation path. Simulations of the algorithm before and after improvement are carried out based on the data retrieved from the Enhanced Magnetic Model (EMM). The performance of the improved method is evaluated and verified in the case of the area with normal geomagnetic field (GF), geomagnetic anomaly area and multiple destinations. The simulation results show that the search efficiency and the straightness of the navigation path are greatly improved. The reason is that the constraint of sample space reduces the randomness in the process of navigation path search, and the improved evaluation function can evaluate the quality of samples more accurately. The improved algorithm also has good performance in the geomagnetic anomaly area, which indicates the potential application in the future.

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Section:  mentioning

confidence: 99%

Section: Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Geomagnetic Gradient-Assisted Evolutionary Algorithm for Long-Range Underwater Navigation

Zhang

Shin

et al. 2021

IEEE Trans. Instrum. Meas.

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“…Geomagnetic fields are a very important cue for navigation by these animals (Zhang et al, 2019 ). At any point on the Earth's surface, geomagnetic fields can be described as vectors in three-dimensional space (see Figure 1 ).…”

Section: Introductionmentioning

confidence: 99%

A Correlation Analysis of Geomagnetic Field Characteristics in Geomagnetic Perceiving Navigation

Jiang

et al. 2021

Front. Neurorobot.

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It is well-known that geomagnetic fields have multiple components or parameters, and that these geomagnetic parameters are related to each other. In this paper, a parameter selection method is proposed, and this paper mainly discusses the correlation of geomagnetic field parameters for geomagnetic navigation technology. For the correlation analysis between geomagnetic parameters, the similarity calculation of the correlation coefficient is firstly introduced for geomagnetic navigation technology, and the grouped results are obtained by data analysis. At the same time, the search algorithm (Hex-path algorithm) is used to verify the correlation analysis results. The results show the same convergent state for the approximate correlation coefficient. In other words, the simulation results are in agreement with the similarity calculation results.

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“…In recent years, field robots have been widely deployed in nuclear plants, agriculture [Kim et al(2019) Kim, Kim, Ju, and Son] and construction, and underwater [Zhang et al(2019) Zhang, Liu, Luo, and Yang], as well as military areas, and their usefulness has attracted a considerable amount of attention from environmental scientists and robotics engineers. However, field robotics research is complicated because agents need to perform tasks or missions in outdoor, unstructured, and unknown environments.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Systems-based Hierarchical Control Architecture for Heterogeneous Field Robot Teams

Ju¹,

Son²

2020

Preprint

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Field robot systems have recently been applied to a wide range of research fields. Making such systems more automated, advanced, and activated requires cooperation among heterogeneous robots. Classic control theory is inefficient in managing large-scale complex dynamic systems. Therefore, the supervisory control theory based on discrete event system needs to be introduced to overcome this limitation. In this study, we propose a hybrid systems-based hierarchical control architecture through a supervisory control-based high-level controller and a traditional control-based low-level controller. The hybrid systems and its dynamics are modeled through a formal method called hybrid automata, and the behavior specifications expressing the control objectives for cooperation are designed. Additionally, a modular supervisor that is more scalable and maintainable than a centralized supervisory controller was synthesized. The proposed hybrid systems and hierarchical control architecture were implemented, validated, and then evaluated for performance through the physics-based simulator. Experimental results confirmed that the heterogeneous field robot team satisfied the given specifications and presented systematic results, validating the efficiency of the proposed control architecture.

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Bio-Inspired Approach for Long-Range Underwater Navigation Using Model Predictive Control

Cited by 31 publications

References 47 publications

Geomagnetic Gradient-Assisted Evolutionary Algorithm for Long-Range Underwater Navigation

Geomagnetic Gradient-Assisted Evolutionary Algorithm for Long-Range Underwater Navigation

A Correlation Analysis of Geomagnetic Field Characteristics in Geomagnetic Perceiving Navigation

A Hybrid Systems-based Hierarchical Control Architecture for Heterogeneous Field Robot Teams

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