Dynamic Path Planning for Unmanned Aerial Vehicles Under Deadline and Sector Capacity Constraints

2021 ◽  
pp. 1-13
Author(s):  
Sudharsan Vaidhun ◽  
Zhishan Guo ◽  
Jiang Bian ◽  
Haoyi Xiong ◽  
Sajal Das
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Capacity Constraints ◽  
Aerial Vehicles ◽  
Dynamic Path Planning ◽  
Dynamic Path

scholarly journals A New Dynamic Path Planning Approach for Unmanned Aerial Vehicles

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Chenxi Huang ◽  
Yisha Lan ◽  
Yuchen Liu ◽  
Wen Zhou ◽  
Hongbin Pei ◽  
...  
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Dynamic Path Planning ◽  
Planning Approach ◽  
Starting Point ◽  
Moving Direction ◽  
Dynamic Path ◽  
The Cost

Dynamic path planning is one of the key procedures for unmanned aerial vehicles (UAV) to successfully fulfill the diversified missions. In this paper, we propose a new algorithm for path planning based on ant colony optimization (ACO) and artificial potential field. In the proposed algorithm, both dynamic threats and static obstacles are taken into account to generate an artificial field representing the environment for collision free path planning. To enhance the path searching efficiency, a coordinate transformation is applied to move the origin of the map to the starting point of the path and in line with the source-destination direction. Cost functions are established to represent the dynamically changing threats, and the cost value is considered as a scalar value of mobile threats which are vectors actually. In the process of searching for an optimal moving direction for UAV, the cost values of path, mobile threats, and total cost are optimized using ant optimization algorithm. The experimental results demonstrated the performance of the new proposed algorithm, which showed that a smoother planning path with the lowest cost for UAVs can be obtained through our algorithm.

Cooperative Path Planning of Unmanned Aerial Vehicles

2010 ◽  
Author(s):  
Antonios Tsourdos ◽  
Brian White ◽  
Madhavan Shanmugavel
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles

scholarly journals Global Dynamic Path Planning Fusion Algorithm Combining Jump-A* Algorithm and Dynamic Window Approach

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 19632-19638
Author(s):  
Lisang Liu ◽  
Jinxin Yao ◽  
Dongwei He ◽  
Jian Chen ◽  
Jing Huang ◽  
...  
Keyword(s):  
Path Planning ◽  
A Algorithm ◽  
Fusion Algorithm ◽  
Global Dynamic ◽  
Dynamic Path Planning ◽  
Dynamic Path ◽  
Window Approach

Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation

2011 ◽  
Vol 142 ◽  
pp. 12-15
Author(s):  
Ping Feng
Keyword(s):  
Path Planning ◽  
Search Algorithm ◽  
Traffic Condition ◽  
Planning Time ◽  
Dynamic Path Planning ◽  
Short Period ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm ◽  
Chaos Genetic Algorithm

The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.

Research on Dynamic Path Planning Algorithm of UAV

2021 ◽  
Author(s):  
Xiujie Yang ◽  
Zhenjun Du ◽  
Deyu Zhang ◽  
Haolei Sun
Keyword(s):  
Path Planning ◽  
Dynamic Path Planning ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm

scholarly journals Local Dynamic Path Planning for an Ambulance Based on Driving Risk and Attraction Field

2021 ◽  
Vol 13 (6) ◽  
pp. 3194
Author(s):  
Fang Zong ◽  
Meng Zeng ◽  
Yang Cao ◽  
Yixuan Liu
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Velocity Potential ◽  
Attractive Potential ◽  
Local Dynamic ◽  
Repulsive Potential ◽  
Ambulance Personnel ◽  
Lane Changing ◽  
Dynamic Path Planning ◽  
Dynamic Path

Path planning is one of the most important aspects for ambulance driving. A local dynamic path planning method based on the potential field theory is presented in this paper. The potential field model includes two components—repulsive potential and attractive potential. Repulsive potential includes road potential, lane potential and obstacle potential. Considering the driving distinction between an ambulance and a regular vehicle, especially in congested traffic, an adaptive potential function for a lane line is constructed in association with traffic conditions. The attractive potential is constructed with target potential, lane-velocity potential and tailgating potential. The design of lane-velocity potential is to characterize the influence of velocity on other lanes so as to prevent unnecessary lane-changing behavior for the sake of time-efficiency. The results obtained from simulation demonstrate that the proposed method yields a good performance for ambulance driving in an urban area, which can provide support for designing an ambulance support system for the ambulance personnel and dispatcher.

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