Coverage path planning algorithms for agricultural field machines

2009 ◽  
Vol 26 (8) ◽  
pp. 651-668 ◽  
Author(s):  
Timo Oksanen ◽  
Arto Visala
Keyword(s):  
Path Planning ◽  
Agricultural Field ◽  
Coverage Path Planning ◽  
Planning Algorithms

scholarly journals Robot Coverage Path Planning under Uncertainty Using Knowledge Inference and Hedge Algebras

Machines ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 46 ◽  
Author(s):  
Hai Van Pham ◽  
Philip Moore
Keyword(s):  
Path Planning ◽  
Environmental Awareness ◽  
Robotic Systems ◽  
Self Awareness ◽  
Coverage Path Planning ◽  
Knowledge Reasoning ◽  
Operating Environments ◽  
Dynamic Operating ◽  
Planning Algorithms ◽  
Autonomous Robotic Systems

Human behaviour demonstrates environmental awareness and self-awareness which is used to arrive at decisions and actions or reach conclusions based on reasoning and inference. Environmental awareness and self-awareness are traits which autonomous robotic systems must have to effectively plan an optimal route and operate in dynamic operating environments. This paper proposes a novel approach to enable autonomous robotic systems to achieve efficient coverage path planning, which combines adaptation with knowledge reasoning techniques and hedge algebras to achieve optimal coverage path planning in multiple decision-making under dynamic operating environments. To evaluate the proposed approach we have implemented it in a mobile cleaning robot. The results demonstrate the ability to avoid static and dynamic (moving) obstacles while achieving efficient coverage path planning with low repetition rates. While alternative current coverage path planning algorithms have achieved acceptable results, our reported results have demonstrated a significant performance improvement over the alternative coverage path planning algorithms.

scholarly journals Research on UAV Path Planning Algorithms

2021 ◽  
Vol 693 (1) ◽  
pp. 012120
Author(s):  
Hao Wang ◽  
Weijun Pan
Keyword(s):  
Path Planning ◽  
Planning Algorithms

scholarly journals R-DFS: A Coverage Path Planning Approach Based on Region Optimal Decomposition

2021 ◽  
Vol 13 (8) ◽  
pp. 1525
Author(s):  
Gang Tang ◽  
Congqiang Tang ◽  
Hao Zhou ◽  
Christophe Claramunt ◽  
Shaoyang Men
Keyword(s):  
Path Planning ◽  
Google Earth ◽  
Simulation Experiments ◽  
Minimum Width ◽  
Coverage Path Planning ◽  
Optimal Paths ◽  
Planning Approach ◽  
Polygonal Area ◽  
Aerial Vehicle ◽  
Working Distance

Most Coverage Path Planning (CPP) strategies based on the minimum width of a concave polygonal area are very likely to generate non-optimal paths with many turns. This paper introduces a CPP method based on a Region Optimal Decomposition (ROD) that overcomes this limitation when applied to the path planning of an Unmanned Aerial Vehicle (UAV) in a port environment. The principle of the approach is to first apply a ROD to a Google Earth image of a port and combining the resulting sub-regions by an improved Depth-First-Search (DFS) algorithm. Finally, a genetic algorithm determines the traversal order of all sub-regions. The simulation experiments show that the combination of ROD and improved DFS algorithm can reduce the number of turns by 4.34%, increase the coverage rate by more than 10%, and shorten the non-working distance by about 29.91%. Overall, the whole approach provides a sound solution for the CPP and operations of UAVs in port environments.

Coverage Path Planning with Proximal Policy Optimization in a Grid-based Environment

2020 ◽  
Author(s):  
Aleksandr Ianenko ◽  
Alexander Artamonov ◽  
Georgii Sarapulov ◽  
Alexey Safaraleev ◽  
Sergey Bogomolov ◽  
...  
Keyword(s):  
Path Planning ◽  
Coverage Path Planning ◽  
Policy Optimization ◽  
Grid Based

A Clustering-Based Coverage Path Planning Method for Autonomous Heterogeneous UAVs

2021 ◽  
pp. 1-11
Author(s):  
Jinchao Chen ◽  
Chenglie Du ◽  
Ying Zhang ◽  
Pengcheng Han ◽  
Wei Wei
Keyword(s):  
Path Planning ◽  
Planning Method ◽  
Coverage Path Planning
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