Autonomous Exploration with a Low-Cost Quadrocopter using Semi-Dense Monocular SLAM Authors: Lukas von Stumberg,
The aim of this Project is the Autonomous Exploration of a Quad rotor using Monocular SLAM. To cover this aim, there is a need of
Keisuke Tateno; Federico Tombari; Iro Laina; Nassir Navab Given the recent advances in depth prediction from Convolutional
The aim of this project is autonomous flight and obstacle avoidance of a Quadrotor using monocular SLAM. To realize the
"CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction," K. Tateno, F. Tombari, I. Laina, N. Navab, IEEE
The autonomous system is optimised to exploration and SLAM, powered by incremental DP-SLAM & Vision based neuromorphic
Direct methods for Visual Odometry (VO) have gained popularity due to their capability to exploit information from all intensity
This video demonstrates the system described in the paper: "Monocular, Real-Time Surface Reconstruction using Dynamic Level of
Multi-Level Mapping: Real-time Dense Monocular SLAM W. Nicholas Greene, Kyel Ok, Peter Lommel, and Nicholas Roy IEEE
sensor-based exploration without using map information.
"Short-term UAV Path-Planning with Monocular-Inertial SLAM in the Loop", Ignacio Alzugaray, Lucas Teixeira and Margarita Chli,
Paper available at: http://ieeexplore.ieee.org/document/8246525/ * Additional demo is available at: https://youtu.be/Dp6XhvQnWp0 *
AR. Drone 2.0 doing fully autonomous navigation and exploration in an unknown environment. 3D mapping and localisation is done
Work done during my Bachelor's thesis.
Project website: http://www.albertpumarola.com/research/pl-slam/ Paper: http://www.albertpumarola.com/publications/files/
This video demonstrate the autonomous exploration of a building by a mobile robot. At the beginning the robot doesn't have any
Christian Mostegel, Andreas Wendel, Horst Bischof, "Active Monocular Localization: Towards Autonomous Monocular Exploration
We address the problem of visual inertial state estimation, control and 3D mapping on platforms with Size, Weight, And Power (
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