Visual Inertial Odometry using Focal Plane Binary Features (BIT-VIO)
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866911988902264832 |
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| author | Lisondra, Matthew Kim, Junseo Murai, Riku Zareinia, Kourosh Saeedi, Sajad |
| author_facet | Lisondra, Matthew Kim, Junseo Murai, Riku Zareinia, Kourosh Saeedi, Sajad |
| contents | Focal-Plane Sensor-Processor Arrays (FPSP)s are an emerging technology that can execute vision algorithms directly on the image sensor. Unlike conventional cameras, FPSPs perform computation on the image plane -- at individual pixels -- enabling high frame rate image processing while consuming low power, making them ideal for mobile robotics. FPSPs, such as the SCAMP-5, use parallel processing and are based on the Single Instruction Multiple Data (SIMD) paradigm. In this paper, we present BIT-VIO, the first Visual Inertial Odometry (VIO) which utilises SCAMP-5.BIT-VIO is a loosely-coupled iterated Extended Kalman Filter (iEKF) which fuses together the visual odometry running fast at 300 FPS with predictions from 400 Hz IMU measurements to provide accurate and smooth trajectories. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_09882 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Visual Inertial Odometry using Focal Plane Binary Features (BIT-VIO) Lisondra, Matthew Kim, Junseo Murai, Riku Zareinia, Kourosh Saeedi, Sajad Robotics Focal-Plane Sensor-Processor Arrays (FPSP)s are an emerging technology that can execute vision algorithms directly on the image sensor. Unlike conventional cameras, FPSPs perform computation on the image plane -- at individual pixels -- enabling high frame rate image processing while consuming low power, making them ideal for mobile robotics. FPSPs, such as the SCAMP-5, use parallel processing and are based on the Single Instruction Multiple Data (SIMD) paradigm. In this paper, we present BIT-VIO, the first Visual Inertial Odometry (VIO) which utilises SCAMP-5.BIT-VIO is a loosely-coupled iterated Extended Kalman Filter (iEKF) which fuses together the visual odometry running fast at 300 FPS with predictions from 400 Hz IMU measurements to provide accurate and smooth trajectories. |
| title | Visual Inertial Odometry using Focal Plane Binary Features (BIT-VIO) |
| topic | Robotics |
| url | https://arxiv.org/abs/2403.09882 |