Name
Title | ||
|---|---|---|
A synchronized visual-inertial sensor system with FPGA pre-processing for accurate real-time SLAM |
Abstract | ||
|---|---|---|
Robust, accurate pose estimation and mapping at real-time in six dimensions is a primary need of mobile robots, in particular flying Micro Aerial Vehicles (MAVs), which still perform their impressive maneuvers mostly in controlled environments. This work presents a visual-inertial sensor unit aimed at effortless deployment on robots in order to equip them with robust real-time Simultaneous Localization and Mapping (SLAM) capabilities, and to facilitate research on this important topic at a low entry barrier. Up to four cameras are interfaced through a modern ARM-FPGA system, along with an Inertial Measurement Unit (IMU) providing high-quality rate gyro and accelerometer measurements, calibrated and hardware-synchronized with the images. This facilitates a tight fusion of visual and inertial cues that leads to a level of robustness and accuracy which is difficult to achieve with purely visual SLAM systems. In addition to raw data, the sensor head provides FPGA-pre-processed data such as visual keypoints, reducing the computational complexity of SLAM algorithms significantly and enabling employment on resource-constrained platforms. Sensor selection, hardware and firmware design, as well as intrinsic and extrinsic calibration are addressed in this work. Results from a tightly coupled reference visual-inertial motion estimation framework demonstrate the capabilities of the presented system. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICRA.2014.6906892 | Robotics and Automation |
Keywords | Field | DocType |
SLAM (robots),acceleration measurement,angular velocity measurement,field programmable gate arrays,inertial navigation,microsensors,mobile robots,pose estimation,real-time systems,robot vision,sensor fusion,signal processing equipment,ARM-FPGA system,FPGA preprocessing,accelerometer measurement,accurate real time SLAM,flying microaerial vehicles,high quality rate gyroscope,inertial measurement unit,mapping capability,mobile robot,pose estimation,real-time robot Localization,reference visual-inertial motion estimation,synchronized visual inertial sensor system,visual-inertial sensor unit,Calibration,Camera,FPGA,IMU,SLAM,Sensor Fusion,Visual-Inertial Motion Estimation | Inertial frame of reference,Computer vision,Field-programmable gate array,Sensor fusion,Control engineering,Sensor system,Inertial measurement unit,Artificial intelligence,Engineering,Computer hardware,Calibration | Conference |
ISSN | Citations | PageRank |
1050-4729 | 49 | 2.84 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolic, J. | 1 | 49 | 2.84 |
| Rehder, J. | 2 | 49 | 2.84 |
| M. Burri | 3 | 343 | 18.62 |
| Gohl, P. | 4 | 49 | 2.84 |