Position and orientation estimation based on Kalman filtering of stereo images

Author(s):  
V. Lippiello ◽  
B. Siciliano ◽  
L. Villani
Author(s):  
Seyed Fakoorian ◽  
Matteo Palieri ◽  
Angel Santamaria-Navarro ◽  
Cataldo Guaragnella ◽  
Dan Simon ◽  
...  

Abstract Accurate attitude estimation using low-cost sensors is an important capability to enable many robotic applications. In this paper, we present a method based on the concept of correntropy in Kalman filtering to estimate the 3D orientation of a rigid body using a low-cost inertial measurement unit (IMU). We then leverage the proposed attitude estimation framework to develop a LiDAR-Intertial Odometry (LIO) demonstrating improved localization accuracy with respect to traditional methods. This is of particular importance when the robot undergoes high-rate motions that typically exacerbate the issues associated with low-cost sensors. The proposed orientation estimation approach is first validated using the data coming from a low-cost IMU sensor. We further demonstrate the performance of the proposed LIO solution in a simulated robotic cave exploration scenario.


Author(s):  
Przemysław Pruszowski ◽  
Agnieszka Szczesna ◽  
Andrzej Polański ◽  
Janusz Słupik ◽  
Konrad Wojciechowski

Author(s):  
Arash Shahmansoori ◽  
Gabriel E. Garcia ◽  
Giuseppe Destino ◽  
Gonzalo Seco-Granados ◽  
Henk Wymeersch

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