Shortest Path Planning of UAV for Target Tracking and Obstacle Avoidance in 3D Environment

2020 ◽  
Author(s):  
Yanxiang Wang ◽  
Honglun Wang ◽  
Yuebin Lun
Keyword(s):  
Path Planning ◽  
Target Tracking ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
3D Environment

scholarly journals Prototyping Non-holonomic Hovercraft for Path Planning and Obstacle Avoidance

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Ghulam -e-Mustafa Abro ◽  
Zain Anwar Ali ◽  
Bazgha Jabeen
Keyword(s):  
Path Planning ◽  
Control Systems ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Digital Image ◽  
Pid Control ◽  
Control Algorithm ◽  
Autonomous Control ◽  
Physical Quantities

— By definition, autonomous control systems are thesystems that sense the physical quantities from their environmentand may execute any dirty, difficult, dull and dangerous taskwithout any intervention. These systems are mostly used in thetransportation of large packages from one place to anotherautonomously by selecting the shortest path, accurate speed andobstacle avoidance. This paper describes the development offuzzy based PID control algorithm to tackle the dynamicconstraints of localization for proposed non-holonomichovercraft. Furthermore, in order to monitor the hovercraft thatwhether it is hovering in a familiar or strange environment;paper suggests the incorporation of digital image processingtechnique which will regularly correlate, the images beingcaptured by the prototype. Moreover, paper methodology alsoprovides the deployment way along with the interfacingtechniques of some configurable sensors, which will share theinformation related to the surroundings of hovercraft usinginternet of things (IoT).

scholarly journals Combining turning point detection and Dijkstra’s algorithm to search the shortest path

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401668335 ◽  
Author(s):  
Ter-Feng Wu ◽  
Pu-Sheng Tsai ◽  
Nien-Tsu Hu ◽  
Jen-Yang Chen
Keyword(s):  
Image Processing ◽  
Path Planning ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Turning Point ◽  
Dijkstra’S Algorithm ◽  
Edge Point ◽  
Dijkstra's Algorithm ◽  
Before And After ◽  
Point Detection

In this study, image processing was combined with path-planning object-avoidance technology to determine the shortest path to the destination. The content of this article comprises two parts: in the first part, image processing was used to establish a model of obstacle distribution in the environment, and boundary sequence permutation method was used to conduct orderly arrangement of edge point coordinates of all objects, to determine linking relationship between each edge point, and to individually classify objects in the image. Then, turning point detection method was used to compare the angle size between vectors before and after each edge point and to determine vertex coordinates of polygonal obstacles. In the second part, a modified Dijkstra’s algorithm was used to turn vertices of convex-shaped obstacles into network nodes, to determine the shortest path by a cost function, and to find an obstacle avoidance path connecting the start and end points. In order to verify the feasibility of the proposed architecture, an obstacle avoidance path simulation was made by the graphical user interface of the programming language MATLAB. The results show that the proposed method in path planning not only is feasible but can also obtain good results.

Delaunay Graph Based Path Planning of Dynamic Obstacle Avoidance Method for Mobile

2011 ◽  
Vol 217-218 ◽  
pp. 1775-1780
Author(s):  
Hui Ying Dong ◽  
Yang Song ◽  
Yu Zhao
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Working Space ◽  
Optimum Path ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Approximate Shortest Path

This paper is about dynamic obstacle avoidance. Delaunay Graph is used for modeling the working space, an approximate shortest path of mobile robot is determined by using floyd algorithm. Path can be found easily with genetic algorithm. Then genetic algorithm is used for obtaining the optimum path. It may meet which dynamic obstacle when robot follows optimum path. so it should avoid it. Results of simulation show that this path planning method is simple and realized easily.

scholarly journals RimJump*: Tangent Based Shortest Path Planning for Cluttered 3D Environment

2021 ◽  
Author(s):  
Zhuo Yao
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Autonomous Vehicles ◽  
Shortest Paths ◽  
Research Area ◽  
Time Cost ◽  
Geometrical Properties ◽  
3D Environment ◽  
Starting Point ◽  
Map Scale

Path planning in 3D environment is a fundamental research area for robots and autonomous vehicles. Based on the principle ``the shortest path consists of tangents'', RimJump* is proposed as a tangent-based path planning method suitable for finding the shortest path (both off-ground and on-ground) in 3D space (e.g., octomap and point cloud) for mobile platform to follow. RimJump* searches the tangent graph in the form of a path tree and considers the geometrical properties of the locally shortest path. Therefore, the method can provide all of the locally shortest paths that connect the starting point and the target, including the globally shortest path. And the time cost of RimJump* is insensitive to map scale increases in comparison to methods that search the whole passable space rather than the surface of the obstacle, e.g., Dijkstra and A*. In the Results, RimJump* is compared with other methods in terms of path length and time cost.

scholarly journals Prototyping Non-holonomic Hovercraft for Path Planning and Obstacle Avoidance

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ghulam -e-Mustafa Abro ◽  
Zain Anwar Ali ◽  
Bazgha Jabeen
Keyword(s):  
Path Planning ◽  
Control Systems ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Digital Image ◽  
Pid Control ◽  
Control Algorithm ◽  
Autonomous Control ◽  
Physical Quantities

— By definition, autonomous control systems are thesystems that sense the physical quantities from their environmentand may execute any dirty, difficult, dull and dangerous taskwithout any intervention. These systems are mostly used in thetransportation of large packages from one place to anotherautonomously by selecting the shortest path, accurate speed andobstacle avoidance. This paper describes the development offuzzy based PID control algorithm to tackle the dynamicconstraints of localization for proposed non-holonomichovercraft. Furthermore, in order to monitor the hovercraft thatwhether it is hovering in a familiar or strange environment;paper suggests the incorporation of digital image processingtechnique which will regularly correlate, the images beingcaptured by the prototype. Moreover, paper methodology alsoprovides the deployment way along with the interfacingtechniques of some configurable sensors, which will share theinformation related to the surroundings of hovercraft usinginternet of things (IoT).

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