Visual Simultaneous Localization and Mapping in a Noisy Static Environment

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  • Visual Simultaneous Localization and Mapping in a Noisy Static Environment Book Detail

  • Author :
  • Release Date : 2019
  • Publisher :
  • Genre : Computer vision
  • Pages : 0
  • ISBN 13 :
  • File Size : 76,76 MB
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Visual Simultaneous Localization and Mapping in a Noisy Static Environment by PDF Summary

Book Description: Simultaneous Localization and Mapping (SLAM) has seen tremendous interest amongst the research community in recent years due to its ability to make the robot truly independent in navigation. Visual Simultaneous Localization and Mapping (VSLAM) is when an autonomous mobile robot is embedded with a vision sensor such as monocular, stereo vision, omnidirectional or Red Green Blue Depth (RGBD) camera to localize and map an unknown environment. The purpose of this research is to address the problem of environmental noise, such as light intensity in a static environment, which has been an issue that makes a Visual Simultaneous Localization and Mapping (VSLAM) system to be ineffective. In this study, we have introduced a Light Filtering Algorithm into the Visual Simultaneous Localization and Mapping (VSLAM) method to reduce the amount of noise in order to improve the robustness of the system in a static environment, together with the Extended Kalman Filter (EKF) algorithm for localization and mapping and A* algorithm for navigation. Simulation is utilized to execute experimental performance.

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