scholarly journals A Review: The Survey of Attitude Estimation in Autonomous UAV Navigation

2019 ◽  
Author(s):  
Zhaomin Ma ◽  
Zhengqiang Chen ◽  
Ling Huang
Keyword(s):  
Attitude Estimation ◽  
Uav Navigation

A geometric framework for rigid body attitude estimation

Automatica ◽  
2021 ◽  
Vol 128 ◽  
pp. 109494
Author(s):  
Yujendra Bharathi Mitikiri ◽  
Kamran Mohseni
Keyword(s):  
Rigid Body ◽  
Attitude Estimation ◽  
Geometric Framework ◽  
Body Attitude

scholarly journals Pose Measurement for Unmanned Aerial Vehicle Based on Rigid Skeleton

2021 ◽  
Vol 11 (4) ◽  
pp. 1373
Author(s):  
Jingyu Zhang ◽  
Zhen Liu ◽  
Guangjun Zhang
Keyword(s):  
Measurement Errors ◽  
Structural Characteristics ◽  
Geometric Model ◽  
Formation Flight ◽  
Depth Information ◽  
Feature Points ◽  
Feature Point Extraction ◽  
Aerial Vehicle ◽  
Uav Navigation ◽  
Rigid Skeleton

Pose measurement is a necessary technology for UAV navigation. Accurate pose measurement is the most important guarantee for a UAV stable flight. UAV pose measurement methods mostly use image matching with aircraft models or 2D points corresponding with 3D points. These methods will lead to pose measurement errors due to inaccurate contour and key feature point extraction. In order to solve these problems, a pose measurement method based on the structural characteristics of aircraft rigid skeleton is proposed in this paper. The depth information is introduced to guide and label the 2D feature points to eliminate the feature mismatch and segment the region. The space points obtained from the marked feature points fit the space linear equation of the rigid skeleton, and the UAV attitude is calculated by combining with the geometric model. This method does not need cooperative identification of the aircraft model, and can stably measure the position and attitude of short-range UAV in various environments. The effectiveness and reliability of the proposed method are verified by experiments on a visual simulation platform. The method proposed can prevent aircraft collision and ensure the safety of UAV navigation in autonomous refueling or formation flight.

scholarly journals UAV navigation using opto-electronic and inertial means in GNSS-denied environment

2021 ◽  
Vol 1925 (1) ◽  
pp. 012051
Author(s):  
A Savkin ◽  
D Antonov ◽  
L Kolganov ◽  
M Ryabinkin ◽  
E Chekhov
Keyword(s):  
Uav Navigation

scholarly journals Drone Deep Reinforcement Learning: A Review

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 999
Author(s):  
Ahmad Taher Azar ◽  
Anis Koubaa ◽  
Nada Ali Mohamed ◽  
Habiba A. Ibrahim ◽  
Zahra Fathy Ibrahim ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
State Of The Art ◽  
Real Life ◽  
Environment Monitoring ◽  
Simulated Environments ◽  
Infrastructure Inspection ◽  
Remote Sensing Mapping ◽  
And Control ◽  
The Military ◽  
Uav Navigation

Unmanned Aerial Vehicles (UAVs) are increasingly being used in many challenging and diversified applications. These applications belong to the civilian and the military fields. To name a few; infrastructure inspection, traffic patrolling, remote sensing, mapping, surveillance, rescuing humans and animals, environment monitoring, and Intelligence, Surveillance, Target Acquisition, and Reconnaissance (ISTAR) operations. However, the use of UAVs in these applications needs a substantial level of autonomy. In other words, UAVs should have the ability to accomplish planned missions in unexpected situations without requiring human intervention. To ensure this level of autonomy, many artificial intelligence algorithms were designed. These algorithms targeted the guidance, navigation, and control (GNC) of UAVs. In this paper, we described the state of the art of one subset of these algorithms: the deep reinforcement learning (DRL) techniques. We made a detailed description of them, and we deduced the current limitations in this area. We noted that most of these DRL methods were designed to ensure stable and smooth UAV navigation by training computer-simulated environments. We realized that further research efforts are needed to address the challenges that restrain their deployment in real-life scenarios.

Reliable attitude estimation algorithm considering atypical observation

2021 ◽  
Vol 65 (10) ◽  
Author(s):  
Xiao-Ting Guo ◽  
Chong Shen ◽  
Jun Tang ◽  
Jie Li ◽  
Jun Liu
Keyword(s):  
Estimation Algorithm ◽  
Attitude Estimation
Sign in / Sign up

Export Citation Format

Share Document