Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/4071
Title: World feature detection and mapping using stereovision and inertial sensors
Authors: Lobo, Jorge 
Queiroz, Carlos 
Dias, Jorge 
Keywords: Inertial sensors; Sensor fusion; 3D reconstruction; Outlier removal
Issue Date: 2003
Keywords: Inertial sensors; Sensor fusion; 3D reconstruction; Outlier removal
Issue Date: 2003
Citation: Robotics and Autonomous Systems. 44:1 (2003) 69-81
Abstract: This paper explores the fusion of inertial information with vision for 3D reconstruction. A method is proposed for vertical line segment detection and subsequent local geometric map building. Visual and inertial sensing are two sensory modalities that can be explored to give robust solutions on image segmentation and recovery of 3D structure from images, increasing the capabilities of autonomous vehicles and enlarging the application potential of vision systems. From the inertial sensors, a camera stereo rig, and a few system parameters we can recover the 3D parameters of the ground plane and vertical lines. The homography between stereo images of ground points can be found. By detecting the vertical line segments in each image, and using the homography of ground points for the foot of each segment, the lines can be matched and reconstructed in 3D. The mobile robot then maps the detected vertical line segments in a world map as it moves. To build this map an outlier removal method is implemented and a statistical approach used, so that a simplified metric map can be obtained for robot navigation.
URI: http://hdl.handle.net/10316/4071
Rights: openAccess
Appears in Collections:FCTUC Eng.Electrotécnica - Artigos em Revistas Internacionais

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