首页|Researchers from University of Toulouse Discuss Findings in Robotics and Automat ion (Sadvio: Sparsify and Densify Vio for Ugv Traversability Estimation)
Researchers from University of Toulouse Discuss Findings in Robotics and Automat ion (Sadvio: Sparsify and Densify Vio for Ugv Traversability Estimation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Robotics - Robotics a nd Automation have been presented. According to news reporting originating from Toulouse, France, by NewsRx correspondents, research stated, “Visual navigation has achieved significant maturity in recent decades. Indirect methods relying on sparse feature extraction, have become a standard for state estimation.” Funders for this research include Centre National D’etudes Spatiales, Occitanie Region. Our news editors obtained a quote from the research from the University of Toulo use, “However, these techniques are not frequently utilized as inputs for path p lanning due to the sparse nature of their maps. To address this limitation, this paper introduces a method to densify the sparse map generated by local indirect Visual or Visual Inertial Odometry (VO-VIO) based on factor graph sparsificatio n. The intended application is the autonomous navigation of Unmaned Ground Vehic les (UGV) in planetary environments without the need to perform computationally expensive dense stereo vision. An incremental 3D mesh is built upon a 2D triangu lation of the features identified by the VO. A photometric consistency check is conducted on each triangle, resulting in a triangle soup rather than a manifold mesh. A dense point cloud is then extracted by casting rays on the triangle soup and using the most reliable triangle to compute depth. Geometric traversability information can subsequently be derived from this point cloud to aid UGV naviga tion.”
ToulouseFranceEuropeRobotics and A utomationRoboticsUniversity of Toulouse
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