A Grid-Map-Oriented UAV Flight Path Planning Algorithm Based on ACO Algorithm

2019 ◽  
pp. 1206-1216
Author(s):  
Wei Tian ◽  
Zhihua Yang
Keyword(s):  
Path Planning ◽  
Flight Path ◽  
Grid Map ◽  
Planning Algorithm ◽  
Path Planning Algorithm

scholarly journals A New Coverage Flight Path Planning Algorithm Based on Footprint Sweep Fitting for Unmanned Aerial Vehicle Navigation in Urban Environments

2019 ◽  
Vol 9 (7) ◽  
pp. 1470 ◽  
Author(s):  
Abdul Majeed ◽  
Sungchang Lee
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicle ◽  
Travelling Salesman Problem ◽  
Urban Environments ◽  
Flight Path ◽  
Computational Time ◽  
Minimum Length ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Path Planning Algorithm

This paper presents a new coverage flight path planning algorithm that finds collision-free, minimum length and flyable paths for unmanned aerial vehicle (UAV) navigation in three-dimensional (3D) urban environments with fixed obstacles for coverage missions. The proposed algorithm significantly reduces computational time, number of turns, and path overlapping while finding a path that passes over all reachable points of an area or volume of interest by using sensor footprints’ sweeps fitting and a sparse waypoint graph in the pathfinding process. We devise a novel footprints’ sweep fitting method considering UAV sensor footprint as coverage unit in the free spaces to achieve maximal coverage with fewer and longer footprints’ sweeps. After footprints’ sweeps fitting, the proposed algorithm determines the visiting sequence of footprints’ sweeps by formulating it as travelling salesman problem (TSP), and ant colony optimization (ACO) algorithm is employed to solve the TSP. Furthermore, we generate a sparse waypoint graph by connecting footprints’ sweeps’ endpoints to obtain a complete coverage flight path. The simulation results obtained from various scenarios fortify the effectiveness of the proposed algorithm and verify the aforementioned claims.

scholarly journals Rapid global path planning algorithm for unmanned surface vehicles in large-scale and multi-island marine environments

2021 ◽  
Vol 7 ◽  
pp. e612
Author(s):  
Dong Wang ◽  
Jie Zhang ◽  
Jiucai Jin ◽  
Deqing Liu ◽  
Xingpeng Mao
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Distance Constraint ◽  
Marine Environments ◽  
Fast Marching ◽  
Unmanned Surface Vehicles ◽  
Grid Map ◽  
Global Path Planning ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A global path planning algorithm for unmanned surface vehicles (USVs) with short time requirements in large-scale and complex multi-island marine environments is proposed. The fast marching method-based path planning for USVs is performed on grid maps, resulting in a decrease in computer efficiency for larger maps. This can be mitigated by improving the algorithm process. In the proposed algorithm, path planning is performed twice in maps with different spatial resolution (SR) grids. The first path planning is performed in a low SR grid map to determine effective regions, and the second is executed in a high SR grid map to rapidly acquire the final high precision global path. In each path planning process, a modified inshore-distance-constraint fast marching square (IDC-FM2) method is applied. Based on this method, the path portions around an obstacle can be constrained within a region determined by two inshore-distance parameters. The path planning results show that the proposed algorithm can generate smooth and safe global paths wherein the portions that bypass obstacles can be flexibly modified. Compared with the path planning based on the IDC-FM2 method applied to a single grid map, this algorithm can significantly improve the calculation efficiency while maintaining the precision of the planned path.

scholarly journals Efficient Energy Flight Path Planning Algorithm Using 3-D Visibility Roadmap for Small Unmanned Aerial Vehicle

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Zahoor Ahmad ◽  
Farman Ullah ◽  
Cong Tran ◽  
Sungchang Lee
Keyword(s):  
Path Planning ◽  
Energy Efficient ◽  
Flight Path ◽  
Considerable Time ◽  
3 Dimensional ◽  
Efficient Energy ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Low Altitude ◽  
Path Planning Algorithm

This paper presents the flight path planning algorithm in a 3-dimensional environment with fixed obstacles for small unmanned aerial vehicles (SUAVs). The emergence of SUAVs for commercial uses with low-altitude flight necessitates efficient flight path planning concerning economical energy consumption. We propose the visibility roadmap based on the visibility graph approach to deal with this uprising problem. The objective is to approximate the collision-free and energy-efficient flight path of SUAVs for flight missions in a considerable time complexity. Stepwise, we describe the construction of the proposed pathfinding algorithm in a convex static obstacle environment. The theoretical analysis and simulation results prove the effectiveness of our method.

scholarly journals A Fast Global Flight Path Planning Algorithm Based on Space Circumscription and Sparse Visibility Graph for Unmanned Aerial Vehicle

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 375 ◽  
Author(s):  
Abdul Majeed ◽  
Sungchang Lee
Keyword(s):  
Path Planning ◽  
Computing Time ◽  
Three Dimensional ◽  
Search Space ◽  
Flight Path ◽  
Visibility Graph ◽  
Planning Algorithm ◽  
Path Lengths ◽  
Path Planning Algorithm ◽  
Obstacle Geometry

This paper proposes a new flight path planning algorithm that finds collision-free, optimal/near-optimal and flyable paths for unmanned aerial vehicles (UAVs) in three-dimensional (3D) environments with fixed obstacles. The proposed algorithm significantly reduces pathfinding computing time without significantly degrading path lengths by using space circumscription and a sparse visibility graph in the pathfinding process. We devise a novel method by exploiting the information about obstacle geometry to circumscribe the search space in the form of a half cylinder from which a working path for UAV can be computed without sacrificing the guarantees on near-optimality and speed. Furthermore, we generate a sparse visibility graph from the circumscribed space and find the initial path, which is subsequently optimized. The proposed algorithm effectively resolves the efficiency and optimality trade-off by searching the path only from the high priority circumscribed space of a map. The simulation results obtained from various maps, and comparison with the existing methods show the effectiveness of the proposed algorithm and verify the aforementioned claims.

scholarly journals Rapid Penetration Path Planning Method for Stealth UAV in Complex Environment with BB Threats

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Zhe Zhang ◽  
Jian Wu ◽  
Jiyang Dai ◽  
Cheng He
Keyword(s):  
Path Planning ◽  
Flight Path ◽  
Complex Environment ◽  
Air Defense ◽  
Penetration Ability ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Dual Base ◽  
Search Approach ◽  
Path Planning Algorithm

This paper presents the flight penetration path planning algorithm in a complex environment with Bogie or Bandit (BB) threats for stealth unmanned aerial vehicle (UAV). The emergence of rigorous air defense radar net necessitates efficient flight path planning and replanning for stealth UAV concerning survivability and penetration ability. We propose the improved A-Star algorithm based on the multiple step search approach to deal with this uprising problem. The objective is to achieve rapid penetration path planning for stealth UAV in a complex environment. Firstly, the combination of single-base radar, dual-base radar, and BB threats is adopted to different threat scenarios which are closer to the real combat environment. Besides, the multistep search strategy, the prediction technique, and path planning algorithm are developed for stealth UAV to deal with BB threats and achieve the penetration path replanning in complex scenarios. Moreover, the attitude angle information is integrated into the flight path which can meet real flight requirements for stealth UAV. The theoretical analysis and numerical results prove the validity of our method.

scholarly journals Multi-Destination Path Planning Method Research of Mobile Robots Based on Goal of Passing through the Fewest Obstacles

2021 ◽  
Vol 11 (16) ◽  
pp. 7378
Author(s):  
Hongchao Zhuang ◽  
Kailun Dong ◽  
Yuming Qi ◽  
Ning Wang ◽  
Lei Dong
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Working Conditions ◽  
Planning Method ◽  
Grid Map ◽  
Global Path Planning ◽  
Planning Algorithm ◽  
Global Planning ◽  
Path Planning Algorithm

In order to effectively solve the inefficient path planning problem of mobile robots traveling in multiple destinations, a multi-destination global path planning algorithm is proposed based on the optimal obstacle value. A grid map is built to simulate the real working environment of mobile robots. Based on the rules of the live chess game in Go, the grid map is optimized and reconstructed. This grid of environment and the obstacle values of grid environment between each two destination points are obtained. Using the simulated annealing strategy, the optimization of multi-destination arrival sequence for the mobile robot is implemented by combining with the obstacle value between two destination points. The optimal mobile node of path planning is gained. According to the Q-learning algorithm, the parameters of the reward function are optimized to obtain the q value of the path. The optimal path of multiple destinations is acquired when mobile robots can pass through the fewest obstacles. The multi-destination path planning simulation of the mobile robot is implemented by MATLAB software (Natick, MA, USA, R2016b) under multiple working conditions. The Pareto numerical graph is obtained. According to comparing multi-destination global planning with single-destination path planning under the multiple working conditions, the length of path in multi-destination global planning is reduced by 22% compared with the average length of the single-destination path planning algorithm. The results show that the multi-destination global path planning method of the mobile robot based on the optimal obstacle value is reasonable and effective. Multi-destination path planning method proposed in this article is conducive to improve the terrain adaptability of mobile robots.

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