Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage
The deep-sea landing vehicle (DSLV) swarm exploration system is a novel platform for the detection of marine mineral resources. A high-precision cooperative localization system with Ultra-Short Baseline (USBL), Doppler Velocity Log (DVL), and electronic compass (EC) plays a vital role in the DSLV sw...
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MDPI AG
2025-02-01
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| author | Zhenzhuo Wei Wei Guo Yanjun Lan Ben Liu Yu Sun Sen Gao |
| author_facet | Zhenzhuo Wei Wei Guo Yanjun Lan Ben Liu Yu Sun Sen Gao |
| author_sort | Zhenzhuo Wei |
| collection | DOAJ |
| description | The deep-sea landing vehicle (DSLV) swarm exploration system is a novel platform for the detection of marine mineral resources. A high-precision cooperative localization system with Ultra-Short Baseline (USBL), Doppler Velocity Log (DVL), and electronic compass (EC) plays a vital role in the DSLV swarm exploration system. However, DVL measurements can be seriously interrupted due to the complex operational underwater environment, leading to unstable localization performance. The accuracy of the cooperative localization system could be further degraded by the persistent rubber track slippage during the vehicle’s movement over the soft seabed. In this study, a data-driven cooperative localization algorithm with a velocity prediction model is proposed to improve the positioning accuracy of DSLV under track slippage. First, a velocity prediction model for DVL measurements is constructed using multi-output least squares support vector regression (MLSSVR), and a genetic algorithm (GA) is further employed to optimize the model’s hyperparameters in order to enhance the robustness of the framework. Furthermore, the outputs of MLSSVR are fed into a DSLV position estimation framework based on the Unscented Kalman Filter (UKF) to improve localization accuracy in the presence of DVL failures. To validate the proposed method, the RecurDyn multibody dynamics simulation platform is applied for data synthesis, accounting for both the impact of the soft seabed and real-world motion simulation. The experimental results indicate that during DVL failure, the proposed algorithm can effectively compensate for the cooperative localization errors caused by track slippage, thereby significantly improving the accuracy and reliability of the DSLV cooperative localization system. |
| format | Article |
| id | doaj-art-6eca0e7a0d444291afd10335efdf03dd |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-6eca0e7a0d444291afd10335efdf03dd2025-08-20T02:53:19ZengMDPI AGRemote Sensing2072-42922025-02-0117575510.3390/rs17050755Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track SlippageZhenzhuo Wei0Wei Guo1Yanjun Lan2Ben Liu3Yu Sun4Sen Gao5Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, ChinaThe deep-sea landing vehicle (DSLV) swarm exploration system is a novel platform for the detection of marine mineral resources. A high-precision cooperative localization system with Ultra-Short Baseline (USBL), Doppler Velocity Log (DVL), and electronic compass (EC) plays a vital role in the DSLV swarm exploration system. However, DVL measurements can be seriously interrupted due to the complex operational underwater environment, leading to unstable localization performance. The accuracy of the cooperative localization system could be further degraded by the persistent rubber track slippage during the vehicle’s movement over the soft seabed. In this study, a data-driven cooperative localization algorithm with a velocity prediction model is proposed to improve the positioning accuracy of DSLV under track slippage. First, a velocity prediction model for DVL measurements is constructed using multi-output least squares support vector regression (MLSSVR), and a genetic algorithm (GA) is further employed to optimize the model’s hyperparameters in order to enhance the robustness of the framework. Furthermore, the outputs of MLSSVR are fed into a DSLV position estimation framework based on the Unscented Kalman Filter (UKF) to improve localization accuracy in the presence of DVL failures. To validate the proposed method, the RecurDyn multibody dynamics simulation platform is applied for data synthesis, accounting for both the impact of the soft seabed and real-world motion simulation. The experimental results indicate that during DVL failure, the proposed algorithm can effectively compensate for the cooperative localization errors caused by track slippage, thereby significantly improving the accuracy and reliability of the DSLV cooperative localization system.https://www.mdpi.com/2072-4292/17/5/755track slippagecooperative localizationDSLVgenetic algorithmmulti-output least squares support vector regression |
| spellingShingle | Zhenzhuo Wei Wei Guo Yanjun Lan Ben Liu Yu Sun Sen Gao Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage Remote Sensing track slippage cooperative localization DSLV genetic algorithm multi-output least squares support vector regression |
| title | Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage |
| title_full | Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage |
| title_fullStr | Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage |
| title_full_unstemmed | Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage |
| title_short | Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage |
| title_sort | data driven cooperative localization algorithm for deep sea landing vehicles under track slippage |
| topic | track slippage cooperative localization DSLV genetic algorithm multi-output least squares support vector regression |
| url | https://www.mdpi.com/2072-4292/17/5/755 |
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