Real-time EKF SLAM system using confidence map of depth information
- Authors
- Choi, J.-W.; Song, H.-K.; Lee, S.-H.; Hong, H.
- Issue Date
- Mar-2016
- Publisher
- Research India Publications
- Keywords
- Confidence map; Extended kalman filter; Stereo vision; Visual SLAM
- Citation
- International Journal of Applied Engineering Research, v.11, no.2, pp 1077 - 1081
- Pages
- 5
- Journal Title
- International Journal of Applied Engineering Research
- Volume
- 11
- Number
- 2
- Start Page
- 1077
- End Page
- 1081
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/8606
- ISSN
- 0973-4562
- Abstract
- Simultaneous localization and mapping (SLAM) is a technique to computationally construct or update a map of an unknown environment while simultaneously tracking a system’s location within the environment. In particular, vision-based SLAM employs a visual camera as a primary sensor. This system attempts to perform simultaneous tracking and feature mapping without additional sensing units, such as a laser sensor, gyroscope, and accelerometers. Stereo-based SLAM employs a stereo rig as the sensing unit, in which a pair of cameras is equipped so that it provides depth information acquired from binocular disparity. In this paper, we introduce a visual SLAM system using a confidence map of the depth estimates of feature points. The confidence map is used as a reliability measure of depth estimates by stereo vision. The experimental results show that the proposed system can obtain stable performance in a dynamic environment. © Research India Publications.
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