Slip Estimation Model for Planetary Rover Using Gaussian Process Regression
Monitoring the rover slip is important; however, a certain level of estimation uncertainty is inevitable. In this paper, we establish slip estimation models for China’s Mars rover, Zhurong, using Gaussian process regression (GPR). The model was able to predict not only the average value of the longi...
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MDPI AG
2022-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/9/4789 |
| _version_ | 1827673114723483648 |
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| author | Tianyi Zhang Song Peng Yang Jia Junkai Sun He Tian Chuliang Yan |
| author_facet | Tianyi Zhang Song Peng Yang Jia Junkai Sun He Tian Chuliang Yan |
| author_sort | Tianyi Zhang |
| collection | DOAJ |
| description | Monitoring the rover slip is important; however, a certain level of estimation uncertainty is inevitable. In this paper, we establish slip estimation models for China’s Mars rover, Zhurong, using Gaussian process regression (GPR). The model was able to predict not only the average value of the longitudinal (slip_<i>x</i>) and lateral slip (slip_<i>y</i>), but also the maximum possible value that slip_<i>x</i> and slip_<i>y</i> could reach. The training data were collected on two simulated soils, TYII-2 and JLU Mars-2, and the GA-BP algorithm was applied as a comparison. The analysis results demonstrated that the soil type and dataset source had a direct impact on the applicability of the slip model on Mars conditions. The properties of the Martian soil near the Zhurong landing site were closer to the JLU Mars-2 simulated soil. The proposed GPR model had high estimation accuracy and estimation potential in slip value, and a 95% confidence interval that the rover could reach during motion. This work was part of a research effort aimed at ensuring the safety of Zhurong. The slip value may be used in subsequent path tracking research, and the slip confidence interval will be able to help guide path planning. |
| first_indexed | 2024-03-10T04:19:25Z |
| format | Article |
| id | doaj.art-e31ebc15c0cb47cea1fac5d08a8f10b1 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T04:19:25Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
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| spelling | doaj.art-e31ebc15c0cb47cea1fac5d08a8f10b12023-11-23T07:53:54ZengMDPI AGApplied Sciences2076-34172022-05-01129478910.3390/app12094789Slip Estimation Model for Planetary Rover Using Gaussian Process RegressionTianyi Zhang0Song Peng1Yang Jia2Junkai Sun3He Tian4Chuliang Yan5School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, ChinaBeijing Institute of Spacecraft System Engineering, China Academy of Space Technology, Beijing 100094, ChinaBeijing Institute of Spacecraft System Engineering, China Academy of Space Technology, Beijing 100094, ChinaSchool of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, ChinaSchool of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, ChinaSchool of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, ChinaMonitoring the rover slip is important; however, a certain level of estimation uncertainty is inevitable. In this paper, we establish slip estimation models for China’s Mars rover, Zhurong, using Gaussian process regression (GPR). The model was able to predict not only the average value of the longitudinal (slip_<i>x</i>) and lateral slip (slip_<i>y</i>), but also the maximum possible value that slip_<i>x</i> and slip_<i>y</i> could reach. The training data were collected on two simulated soils, TYII-2 and JLU Mars-2, and the GA-BP algorithm was applied as a comparison. The analysis results demonstrated that the soil type and dataset source had a direct impact on the applicability of the slip model on Mars conditions. The properties of the Martian soil near the Zhurong landing site were closer to the JLU Mars-2 simulated soil. The proposed GPR model had high estimation accuracy and estimation potential in slip value, and a 95% confidence interval that the rover could reach during motion. This work was part of a research effort aimed at ensuring the safety of Zhurong. The slip value may be used in subsequent path tracking research, and the slip confidence interval will be able to help guide path planning.https://www.mdpi.com/2076-3417/12/9/4789Mars rover Zhuronglongitudinal sliplateral slipGaussian process regressionslip uncertainty |
| spellingShingle | Tianyi Zhang Song Peng Yang Jia Junkai Sun He Tian Chuliang Yan Slip Estimation Model for Planetary Rover Using Gaussian Process Regression Applied Sciences Mars rover Zhurong longitudinal slip lateral slip Gaussian process regression slip uncertainty |
| title | Slip Estimation Model for Planetary Rover Using Gaussian Process Regression |
| title_full | Slip Estimation Model for Planetary Rover Using Gaussian Process Regression |
| title_fullStr | Slip Estimation Model for Planetary Rover Using Gaussian Process Regression |
| title_full_unstemmed | Slip Estimation Model for Planetary Rover Using Gaussian Process Regression |
| title_short | Slip Estimation Model for Planetary Rover Using Gaussian Process Regression |
| title_sort | slip estimation model for planetary rover using gaussian process regression |
| topic | Mars rover Zhurong longitudinal slip lateral slip Gaussian process regression slip uncertainty |
| url | https://www.mdpi.com/2076-3417/12/9/4789 |
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