Structure-Invariant Range-Visual-Inertial Odometry
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866909307904196608 |
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| author | Alberico, Ivan Delaune, Jeff Cioffi, Giovanni Scaramuzza, Davide |
| author_facet | Alberico, Ivan Delaune, Jeff Cioffi, Giovanni Scaramuzza, Davide |
| contents | The Mars Science Helicopter (MSH) mission aims to deploy the next generation of unmanned helicopters on Mars, targeting landing sites in highly irregular terrain such as Valles Marineris, the largest canyons in the Solar system with elevation variances of up to 8000 meters. Unlike its predecessor, the Mars 2020 mission, which relied on a state estimation system assuming planar terrain, MSH requires a novel approach due to the complex topography of the landing site. This work introduces a novel range-visual-inertial odometry system tailored for the unique challenges of the MSH mission. Our system extends the state-of-the-art xVIO framework by fusing consistent range information with visual and inertial measurements, preventing metric scale drift in the absence of visual-inertial excitation (mono camera and constant velocity descent), and enabling landing on any terrain structure, without requiring any planar terrain assumption. Through extensive testing in image-based simulations using actual terrain structure and textures collected in Mars orbit, we demonstrate that our range-VIO approach estimates terrain-relative velocity meeting the stringent mission requirements, and outperforming existing methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_04633 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Structure-Invariant Range-Visual-Inertial Odometry Alberico, Ivan Delaune, Jeff Cioffi, Giovanni Scaramuzza, Davide Robotics Computer Vision and Pattern Recognition The Mars Science Helicopter (MSH) mission aims to deploy the next generation of unmanned helicopters on Mars, targeting landing sites in highly irregular terrain such as Valles Marineris, the largest canyons in the Solar system with elevation variances of up to 8000 meters. Unlike its predecessor, the Mars 2020 mission, which relied on a state estimation system assuming planar terrain, MSH requires a novel approach due to the complex topography of the landing site. This work introduces a novel range-visual-inertial odometry system tailored for the unique challenges of the MSH mission. Our system extends the state-of-the-art xVIO framework by fusing consistent range information with visual and inertial measurements, preventing metric scale drift in the absence of visual-inertial excitation (mono camera and constant velocity descent), and enabling landing on any terrain structure, without requiring any planar terrain assumption. Through extensive testing in image-based simulations using actual terrain structure and textures collected in Mars orbit, we demonstrate that our range-VIO approach estimates terrain-relative velocity meeting the stringent mission requirements, and outperforming existing methods. |
| title | Structure-Invariant Range-Visual-Inertial Odometry |
| topic | Robotics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2409.04633 |