Name
Abstract | ||
|---|---|---|
We present a novel pose and posture estimation framework of aerial skeleton system for outdoor flying. To exploit redundant/independent sensing while rendering the system “modular”, we attach an IMU (inertial measurement unit) sensor and a GNSS (global navigation satellite system) module on each link and perform SE(3)-motion EKF (extended Kalman filtering). We then apply the kinematic constraints of the aerial skeleton system to these EKF estimates of all the links through SCKF (smoothly constrained Kalman filtering), thereby, enforcing the kinematic coherency of the skeleton system and, consequently, significantly enhancing the estimation accuracy and the control performance/stability of the aerial skeleton system. A semi-distributed version of the obtained estimation framework is also presented to address the issue of scalability. The theory is then verified/demonstrated with real outdoor flying experiments and simulation studies of a three-link aerial skeleton system. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICRA.2019.8794080 | 2019 International Conference on Robotics and Automation (ICRA) |
Keywords | Field | DocType |
outdoor flying,posture estimation framework,system modular,GNSS module,global navigation satellite system,EKF estimates,three-link aerial skeleton system,inertial measurement unit,extended Kalman filtering | Computer vision,Extended Kalman filter,Kinematics,Satellite system,Control engineering,Kalman filter,GNSS applications,Inertial measurement unit,Artificial intelligence,Engineering,Rendering (computer graphics),Scalability | Conference |
Volume | Issue | ISSN |
2019 | 1 | 1050-4729 |
ISBN | Citations | PageRank |
978-1-5386-8176-3 | 3 | 0.52 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sangyul Park | 1 | 6 | 1.98 |
| Yonghan Lee | 2 | 3 | 2.88 |
| Jinuk Heo | 3 | 3 | 0.85 |
| Dongjun Lee | 4 | 5 | 2.57 |