Visual Inertial Odometry using Focal Plane Binary Features (BIT-VIO)
arXiv:2403.09882 · doi:10.1109/ICRA57147.2024.10610838
Abstract
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.
Accepted for Presentation Yokohama, Japan for IEEE 2024 ICRA
References in corpus (8)
- ORB-SLAM: a Versatile and Accurate Monocular SLAM System
- VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
- On-Manifold Preintegration for Real-Time Visual-Inertial Odometry
- Ultimate SLAM? Combining Events, Images, and IMU for Robust Visual SLAM in HDR and High Speed Scenarios
- Continuous-Time Visual-Inertial Odometry for Event Cameras
- Navigating the Landscape for Real-time Localisation and Mapping for Robotics and Virtual and Augmented Reality
- BIT-VO: Visual Odometry at 300 FPS using Binary Features from the Focal Plane
- Direct Servo Control from In-Sensor CNN Inference with A Pixel Processor Array