Monocular‐SLAM–based navigation for autonomous micro helicopters in GPS‐denied environments

By Stephan Weiss, Davide Scaramuzza, Roland Yves Siegwart. J. Field Robotics, 2011

466 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/6eb662ef35ec514429c5ba533b212a3a512c3517

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

In Ocean Engineering

Citations in the corpus

Opportunities and challenges with autonomous micro aerial vehicles (2012, methodology): “Similarly, full pose estimation and localization of ground terrain in GPSdenied environments via off-board processing of monocular camera and IMU sensor data is presented by Bourquardez et al. (2009), Blosch et al. (2010), Weiss et al. (2011), and Milford et al. (2011).”
Estimation, Control, and Planning for Aggressive Flight With a Small Quadrotor With a Single Camera and IMU (2017, unknown): “The system dynamic model is ẋ = v,mv̇ = Rτe3 −mge3 , Ṙ = RΩ̂,JΩ̇ + Ω × JΩ = M , (1) 1www.ros.org where x ∈ R3 is the Cartesian position of the vehicle expressed in the inertial frame, v ∈ R3 is the velocity of the vehicle in the inertial frame, m ∈ R is the mass, Ω ∈ R3 is the angular velocity…”
Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows (2018, unknown): “The main advantage of machine vision imagery is that it can be used in rigorous photogrammetric modeling [104], SfM [105], or simultaneous localization and mapping (SLAM) [106] workflows to extract 3D terrain information and pose information simultaneously.”
Comprehensive Simulation of Quadrotor UAVs Using ROS and Gazebo (2012, methodology): “Visual SLAM To demonstrate simulated image based state estimation, we deploy a modified version [22] of the original PTAM system [13] for visual SLAM.”
Unmanned Aircraft Capture and Control Via GPS Spoofing (2014, background): “But given the fragility of GPS and other globalnavigationsatellitesystem(GNSS)signalsundercon-ditionsofsignalblockageorjamming,thereiscurrently great interest in developing UAV navigation and control systems that can operate in GNSS-denied environments (Bachrach, Prentice, He, & Roy, 2011; Garratt a”
Vision-Controlled Micro Flying Robots: From System Design to Autonomous Navigation and Mapping in GPS-Denied Environments (2014, background): “However, the first use of visual SLAM to enable autonomous basic maneuvers—such as take-off and landing, point-to-point navigation, and drift-free hovering on the spot—was done right within the framework of the SFLY project [13], [14].”