Autonomous aerial navigation using monocular visual‐inertial fusion

By Yi Lin, Fei Gao, Tong Qin, Wenliang Gao, Tianbo Liu, William Wu, Zhenfei Yang, Shaojie Shen. 2018

227 citations recorded by the source corpus.

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

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In Aerospace Engineering

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Citations in the corpus

A 64-mW DNN-Based Visual Navigation Engine for Autonomous Nano-Drones (2018, background): “However, commercial nano-UAVs still lack the autonomy boasted by their larger counterparts [1], [8], [9], [10], since their computational capabilities, heavily constrained by their tiny power envelopes, have been considered so far to be totally inadequate for the execution of sophisticated AI worklo”
RTAB‐Map as an open‐source lidar and visual simultaneous localization and mapping library for large‐scale and long‐term online operation (2018, background): “(cid:129) maplab (Schneider et al., 2018) and VINS ‐ Mono (Yi et al., 2017) have (cid:129) ORB ‐ SLAM2 (Mur ‐ Artal & Tardós, 2017) and stereo parallel tracking and mapping (S ‐ PTAM) (Pire et al., 2017) are currently two of the best state ‐ of ‐ the ‐ art feature ‐ based visual SLAM approaches that”
Visual-Inertial Navigation Algorithm Development Using Photorealistic Camera Simulation in the Loop (2018, methodology): “by an IMU [8], using an off-the-shelf pose estimate from an RGB-D sensor (Google Tango) [7], and a factor graph based approach similar to our own [30].”
A Survey on Aerial Swarm Robotics (2018, background): “While dense representations can be directly used for autonomous navigation [186] or geographical reference, sparse representations are often only used for state estimation [187] or collaborative control of robotic agents.”
Visual-Inertial Teach and Repeat for Aerial Inspection (2018, background): “the visual-inertial navigation system presented in [11] autonomous robots are able to perform more challenging tasks.”
RAPTOR: Robust and Perception-Aware Trajectory Replanning for Quadrotor Fast Flight (2020, methodology): “In [12, 13], the optimization is combined with an informed sampling-based path searching to improve the success rate.”