SLAM solution based on particle filter with outliers filtering in dynamic environments

Our work presents a proposal for SLAM (Simultaneous Localization and Mapping) problem in dynamic environments. A method for robot self-localization is described. During operations in dynamic environments, only static landmarks are used. For this purpose, an outliers filter was designed. It separates...

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Bibliographic Details
Main Authors: Vidal, Fabio Silveira, de Oliveira Palmerim Barcelos, Andre, Ferreira Rosa, Paulo Fernando
Format: Conference Proceeding
Language:English
Subjects:
Cameras
Dynamics
Filtering
Hardware
Landmarks
Mobile communication
Outliers (statistics)
Platforms
Robot kinematics
Robot vision systems
Robots
Simultaneous localization and mapping
Trajectory
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Description
Summary:Our work presents a proposal for SLAM (Simultaneous Localization and Mapping) problem in dynamic environments. A method for robot self-localization is described. During operations in dynamic environments, only static landmarks are used. For this purpose, an outliers filter was designed. It separates static and mobile landmarks that are included in a set of neglectable marks. A modified particle filter is proposed which estimates the pose of a robot by a new way. Furthermore, it resamples a new set of particles at each estimative of the pose of the robot. Set of particles is based on current observations made by robot using RGBD camera. ROS (Robot Operating System) platform is used in order to integrate all hardware and our application.
ISSN:2163-5137
2163-5145
DOI:10.1109/ISIE.2015.7281544