EKF and Computer Vision for Mobile Robot Localization
- Resource Type
- Conference
- Authors
- Coelho, Fabricio O.; Carvalho, Joao P.; Pinto, Milena F.; Marcato, Andre L.
- Source
- 2018 13th APCA International Conference on Automatic Control and Soft Computing (CONTROLO) Automatic Control and Soft Computing (CONTROLO), 2018 13th APCA International Conference on. :148-153 Jun, 2018
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Cameras
Mobile robots
Robot vision systems
Computer vision
Computer Vision
Extendend Kalman Filter
Localization
Mobile Robots
- Language
- ISSN
- 2472-8489
The autonomous robotic system accurate localization is a challenging step in robot navigation field once the mobile device should avoid dangerous situations, such as unsafe conditions and collisions. In this context, the present paper proposes a localization method using the Extended Kalman Filter (EKF) to fuse the information coming from two different sensors (i.e. odometry and computer vision). The localization results present with known and unknown starting points and are tested in a simulated environment.