A spacecraft visual navigation algorithm based on mode constraints

2016 ◽  
Author(s):  
Hua Bing ◽  
Wu Yunhua ◽  
Xiongzhi ◽  
Jiang Chun
Keyword(s):  
Visual Navigation ◽  
Navigation Algorithm

scholarly journals Navigation Simulation of a Mecanum Wheel Mobile Robot Based on an Improved A* Algorithm in Unity3D

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2976 ◽  
Author(s):  
Yunwang Li ◽  
Sumei Dai ◽  
Yong Shi ◽  
Lala Zhao ◽  
Minghua Ding
Keyword(s):  
Mobile Robot ◽  
Effective Means ◽  
Three Dimensional ◽  
Simulation Method ◽  
Virtual Prototype ◽  
Visual Navigation ◽  
A Algorithm ◽  
Navigation Algorithm ◽  
Navigation Simulation ◽  
Mecanum Wheel

Computer simulation is an effective means for the research of robot navigation algorithms. In order to implement real-time, three-dimensional, and visual navigation algorithm simulation, a method of algorithm simulation based on secondary development of Unity3D is proposed. With this method, a virtual robot prototype can be created quickly with the imported 3D robot model, virtual joints, and virtual sensors, and then the navigation simulation can be carried out using the virtual prototype with the algorithm script in the virtual environment. Firstly, the scripts of the virtual revolute joint, virtual LiDAR sensors, and terrain environment are written. Secondly, the A* algorithm is improved for navigation in unknown 3D space. Thirdly, taking the Mecanum wheel mobile robot as an example, the 3D robot model is imported into Unity3D, and the virtual joint, sensor, and navigation algorithm scripts are added to the model. Then, the navigation is simulated in static and dynamic environments using a virtual prototype. Finally, the navigation tests of the physical robot are carried out in the physical environment, and the test trajectory is compared with the simulation trajectory. The simulation and test results validate the algorithm simulation method based on the redevelopment of Unity3d, showing that it is feasible, efficient, and flexible.

scholarly journals Visual navigation algorithm for asteroid lander based on irregular curve matching

2021 ◽  
Vol 52 (1) ◽  
pp. 214510
Author(s):  
Wei SHAO ◽  
BoNing WANG ◽  
LingFei DOU ◽  
HanXue ZHAO ◽  
JinCheng XIE ◽  
...  
Keyword(s):  
Visual Navigation ◽  
Curve Matching ◽  
Navigation Algorithm

Research on visual navigation algorithm of AGV used in the small agile warehouse

2017 ◽  
Author(s):  
Wu Chun-Fu ◽  
Wang Xiao-Long ◽  
Chen Qing-Xie ◽  
Cai Xiao-Wei ◽  
Li Guo-Dong
Keyword(s):  
Visual Navigation ◽  
Navigation Algorithm

Visual navigation algorithm based on line geomorphic feature matching for Mars landing

2020 ◽  
Vol 173 ◽  
pp. 383-391
Author(s):  
Wei Shao ◽  
Liang Cao ◽  
Wei Guo ◽  
Jincheng Xie ◽  
Tianhao Gu
Keyword(s):  
Feature Matching ◽  
Visual Navigation ◽  
Navigation Algorithm ◽  
Geomorphic Feature ◽  
On Line

scholarly journals Solution of problem of returning to the starting point of autonomously flying UAV by visual navigation

Informatics ◽  
2020 ◽  
Vol 17 (2) ◽  
pp. 17-24
Author(s):  
R. S. Zhuk ◽  
B. A. Zalesky ◽  
Ph. S. Trotski
Keyword(s):  
Visual Odometry ◽  
Video Camera ◽  
Visual Navigation ◽  
Navigation Algorithm ◽  
Localization And Mapping ◽  
Starting Point ◽  
Navigation Algorithms ◽  
Aerial Vehicle ◽  
Navigation Signals ◽  
The Moment

An autonomous visual navigation algorithm is considered, designed for “home“ return of unmanned aerial vehicle (UAV) equipped with on-board video camera and on-board computer, out of GPS and GLONASS navigation signals. The proposed algorithm is similar to the well-known visual navigation algorithms such as V-SLAM (simultaneous localization and mapping) and visual odometry, however, it differs in separate implementation of mapping and localization processes. It calculates the geographical coordinates of the features on the frames taken by on-board video camera during the flight from the start point until the moment of GPS and GLONASS signals loss. After the loss of the signal the return mission is launched, which provides estimation of the position of UAV relatively the map created by previously found features. Proposed approach does not require such complex calculations as V-SLAM and does not accumulate errors over time, in contrast to visual odometry and traditional methods of inertial navigation. The algorithm was implemented and tested with use of DJI Phantom 3 Pro quadcopter.

Entropy Flow-Aided Navigation

2010 ◽  
Vol 64 (1) ◽  
pp. 109-125 ◽  
Author(s):  
He Deng ◽  
Chao Pan ◽  
Tongxin Wen ◽  
Jianguo Liu
Keyword(s):  
Visual Navigation ◽  
Global Motion ◽  
Computational Accuracy ◽  
Entropy Flow ◽  
Topographic Features ◽  
Navigation Algorithm ◽  
Flying Insects ◽  
New Concepts ◽  
Nonlinear Kalman Filter ◽  
The Cost

Integrating the visual navigation mechanism of flying insects with a nonlinear Kalman filter, this paper proposes a novel navigation algorithm. New concepts of entropic map and entropy flow are presented, which can characterize topographic features and measure changes of the image respectively. Meanwhile, an auto-selecting algorithm of assessment threshold is proposed to improve computational accuracy and efficiency of global motion estimation. The simulation results suggest that the navigation algorithm can perform real-time rectification of the missile's trajectory well, and can reduce the cost of the missile's hardware.

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