ORB-SLAM with Near-infrared images and Optical Flow data
Antonio Buemi, Arcangelo Bruna, Sylvain Petinot, Nicolas Le Roux
- Year
- 2021
- Citations
- 4
Abstract
The algorithms designed to solve the Simultaneous Localization And Mapping (SLAM) problem have to be often executed on embedded platforms in order to become part of complex robotics systems. Despite the continuous growth of their computational capabilities, the embedded devices still have considerable limitations, especially in terms of memory. This paper presents a modified version of the well known ORB-SLAM algorithm which improves its performance thanks to the use of Hardware-generated Optical Flow (HW-OF). The ORB-SLAM has been modified in order to run into the Stereo-cam embedded system by STMi-croelectronics. The Stereo-cam includes the VD56G3 sensor, able to provide Near Infrared (NIR) images and OF data computed by a hardware accelerator. The experiments showed an improvement of the ORB-SLAM performances in terms of memory consumption and frame rate.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002