Event-Based Slip Estimation Framework for Space Rovers Traversing Soft Terrains
Estimating terrain-induced longitudinal slip poses a significant challenge in space rover navigation, particularly when traversing soft terrains in low-light conditions. Precise estimation of this slip is important for rover navigation algorithms, as it helps to prevent rovers from traversing areas...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10613755/ |
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| author | Ruqayya Alhammadi Yahya Zweiri Ahmad Abubakar Mubarak Yakubu Laith Abuassi Lakmal Seneviratne |
| author_facet | Ruqayya Alhammadi Yahya Zweiri Ahmad Abubakar Mubarak Yakubu Laith Abuassi Lakmal Seneviratne |
| author_sort | Ruqayya Alhammadi |
| collection | DOAJ |
| description | Estimating terrain-induced longitudinal slip poses a significant challenge in space rover navigation, particularly when traversing soft terrains in low-light conditions. Precise estimation of this slip is important for rover navigation algorithms, as it helps to prevent rovers from traversing areas with excessive slippage, thereby avoiding entrapment —an outcome that could lead to mission failure. This paper presents a novel event-based longitudinal slip estimation framework designed to operate in low-light conditions. Existing vision-based slip estimation techniques suffer from low temporal resolution sensors and a high sensitivity to motion blur. These limitations prevent the immediate detection of slip events, which can occur in microseconds, making such methods unsuitable for highly variable terrain environments such as lunar surfaces. Our proposed framework addresses these challenges, offering a robust solution for precise slip estimation in microseconds with limited energy consumption. Specifically, we generate the data directly from real-time wheel traces at varied light conditions and motion patterns and then propose a framework to estimate the slip. This framework consists of a denoising filter and a Hough transformer. Experiments conducted on a single-wheel test rig demonstrate the effectiveness of the proposed event-based framework in estimating slip ratios that range from 2% to 90% with an estimated accuracy of above 95% in well-lit conditions and above 94% in low-light conditions. A supplementary video is available at <uri>https://youtu.be/eac6Q2a8A9g</uri>. |
| format | Article |
| id | doaj-art-520486c5686a4a8eba77e5ebd6e7e277 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-520486c5686a4a8eba77e5ebd6e7e2772025-01-21T00:01:00ZengIEEEIEEE Access2169-35362025-01-0113103861039710.1109/ACCESS.2024.343471910613755Event-Based Slip Estimation Framework for Space Rovers Traversing Soft TerrainsRuqayya Alhammadi0https://orcid.org/0000-0001-5413-8708Yahya Zweiri1https://orcid.org/0000-0003-4331-7254Ahmad Abubakar2https://orcid.org/0000-0002-3966-5881Mubarak Yakubu3https://orcid.org/0000-0002-9403-6770Laith Abuassi4Lakmal Seneviratne5https://orcid.org/0000-0001-6405-8402Khalifa University Center for Autonomous and Robotic Systems (KUCARS), Khalifa University, Abu Dhabi, United Arab EmiratesAdvanced Research and Innovation Center (ARIC), Abu Dhabi, United Arab EmiratesKhalifa University Center for Autonomous and Robotic Systems (KUCARS), Khalifa University, Abu Dhabi, United Arab EmiratesKhalifa University Center for Autonomous and Robotic Systems (KUCARS), Khalifa University, Abu Dhabi, United Arab EmiratesKhalifa University Center for Autonomous and Robotic Systems (KUCARS), Khalifa University, Abu Dhabi, United Arab EmiratesKhalifa University Center for Autonomous and Robotic Systems (KUCARS), Khalifa University, Abu Dhabi, United Arab EmiratesEstimating terrain-induced longitudinal slip poses a significant challenge in space rover navigation, particularly when traversing soft terrains in low-light conditions. Precise estimation of this slip is important for rover navigation algorithms, as it helps to prevent rovers from traversing areas with excessive slippage, thereby avoiding entrapment —an outcome that could lead to mission failure. This paper presents a novel event-based longitudinal slip estimation framework designed to operate in low-light conditions. Existing vision-based slip estimation techniques suffer from low temporal resolution sensors and a high sensitivity to motion blur. These limitations prevent the immediate detection of slip events, which can occur in microseconds, making such methods unsuitable for highly variable terrain environments such as lunar surfaces. Our proposed framework addresses these challenges, offering a robust solution for precise slip estimation in microseconds with limited energy consumption. Specifically, we generate the data directly from real-time wheel traces at varied light conditions and motion patterns and then propose a framework to estimate the slip. This framework consists of a denoising filter and a Hough transformer. Experiments conducted on a single-wheel test rig demonstrate the effectiveness of the proposed event-based framework in estimating slip ratios that range from 2% to 90% with an estimated accuracy of above 95% in well-lit conditions and above 94% in low-light conditions. A supplementary video is available at <uri>https://youtu.be/eac6Q2a8A9g</uri>.https://ieeexplore.ieee.org/document/10613755/Neuoromorhic vision sensorevent-basedslip estimationspace roverssoft terrainslow-light |
| spellingShingle | Ruqayya Alhammadi Yahya Zweiri Ahmad Abubakar Mubarak Yakubu Laith Abuassi Lakmal Seneviratne Event-Based Slip Estimation Framework for Space Rovers Traversing Soft Terrains IEEE Access Neuoromorhic vision sensor event-based slip estimation space rovers soft terrains low-light |
| title | Event-Based Slip Estimation Framework for Space Rovers Traversing Soft Terrains |
| title_full | Event-Based Slip Estimation Framework for Space Rovers Traversing Soft Terrains |
| title_fullStr | Event-Based Slip Estimation Framework for Space Rovers Traversing Soft Terrains |
| title_full_unstemmed | Event-Based Slip Estimation Framework for Space Rovers Traversing Soft Terrains |
| title_short | Event-Based Slip Estimation Framework for Space Rovers Traversing Soft Terrains |
| title_sort | event based slip estimation framework for space rovers traversing soft terrains |
| topic | Neuoromorhic vision sensor event-based slip estimation space rovers soft terrains low-light |
| url | https://ieeexplore.ieee.org/document/10613755/ |
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