Abstract
This study propose the use of heterogeneous visual landmarks, points and line segments, to achieve effective cooperation in indoor SLAM environments. In order to achieve un-delayed initialization required by the bearing-only observations, the well-known inverse-depth parameterization is adopted to estimate 3D points. Similarly, to estimate 3D line segments, we present a novel parameterization based on anchored Plücker coordinates, to which extensible endpoints are added
Highlights
Most sensors used for simultaneous localization and mapping (SLAM) operation such as laser range finder, IR and Star Gazer are expensive or needed some artificial markers for the sensing
Contrary to the standard extended Kalman filter (EKF), where estimates are always referred to a world reference frame, the sensor-centred approach represents all feature locations and the camera motion in a reference frame local to the current camera
In this work, we propose the use of heterogeneous visual landmarks, points and line segments, to achieve effective cooperation in indoor SLAM environments
Summary
Most sensors used for SLAM operation such as laser range finder, IR and Star Gazer are expensive or needed some artificial markers for the sensing. CCD camera can reduce cost of production of robot because it is relatively cheap and able to directly use natural markers which cover environment enables its broader application range. Point features have been most used as landmarks for vision sensors due to the fact that it facilitates its general use and application. A solution to the SLAM problem has been seen as a “holy grail” for the mobile robotics community as it would provide the means to make a robot truly autonomous [1]. This paper introduced a vision-based SLAM system that used both of point and line feature for mobile robots in indoor environment
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