The research and realization of the shortest path planning algorithms in map navigation area

2015 ◽  
pp. 379-384
Author(s):  
Shuhao Wen ◽  
Guangzhao Feng ◽  
Jinyu Zhan ◽  
Ming Sun
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Planning Algorithms

scholarly journals Any-Angle Path Planning

AI Magazine ◽  
2013 ◽  
Vol 34 (4) ◽  
pp. 85-107 ◽  
Author(s):  
Alex Nash ◽  
Sven Koenig
Keyword(s):  
Video Games ◽  
Path Planning ◽  
Shortest Path ◽  
Grid Cells ◽  
Grid Graph ◽  
Planning Algorithm ◽  
Planning Algorithms ◽  
Planning Methodology ◽  
Path Planning Algorithm

In robotics and video games, one often discretizes continuous terrain into a grid with blocked and unblocked grid cells and then uses path-planning algorithms to find a shortest path on the resulting grid graph. This path, however, is typically not a shortest path in the continuous terrain. In this overview article, we discuss a path-planning methodology for quickly finding paths in continuous terrain that are typically shorter than shortest grid paths. Any-angle path-planning algorithms are variants of the heuristic path-planning algorithm A* that find short paths by propagating information along grid edges (like A*, to be fast) without constraining the resulting paths to grid edges (unlike A*, to find short paths).

Overview of Path-Planning and Obstacle Avoidance Algorithms for UAVs: A Comparative Study

2018 ◽  
Vol 06 (02) ◽  
pp. 95-118 ◽  
Author(s):  
Mohammadreza Radmanesh ◽  
Manish Kumar ◽  
Paul H. Guentert ◽  
Mohammad Sarim
Keyword(s):  
Path Planning ◽  
Comparative Study ◽  
Operating Conditions ◽  
Computational Time ◽  
Safe Operation ◽  
Sense And Avoid ◽  
Planning Algorithms ◽  
And Control ◽  
Global And Local ◽  
Further Development

Unmanned aerial vehicles (UAVs) have recently attracted the attention of researchers due to their numerous potential civilian applications. However, current robot navigation technologies need further development for efficient application to various scenarios. One key issue is the “Sense and Avoid” capability, currently of immense interest to researchers. Such a capability is required for safe operation of UAVs in civilian domain. For autonomous decision making and control of UAVs, several path-planning and navigation algorithms have been proposed. This is a challenging task to be carried out in a 3D environment, especially while accounting for sensor noise, uncertainties in operating conditions, and real-time applicability. Heuristic and non-heuristic or exact techniques are the two solution methodologies that categorize path-planning algorithms. The aim of this paper is to carry out a comprehensive and comparative study of existing UAV path-planning algorithms for both methods. Three different obstacle scenarios test the performance of each algorithm. We have compared the computational time and solution optimality, and tested each algorithm with variations in the availability of global and local obstacle information.

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