Terrain-Shape-Adaptive Coverage Path Planning With Traversability Analysis

被引:2
|
作者
Qiu, Wenwei [1 ]
Zhou, Dacheng [1 ]
Hui, Wenbo [1 ]
Kwabena, Afimbo Reuben [1 ]
Xing, Yubo [1 ]
Qian, Yi [1 ]
Li, Quan [1 ]
Pu, Huayan [1 ]
Xie, Yangmin [1 ,2 ]
机构
[1] Shanghai Univ, Sch Mechatron Engn & Automat, 99 Shangda Rd, Shanghai 200444, Peoples R China
[2] Shanghai Key Lab Intelligent Mfg & Robot, 99 Shangda Rd, Shanghai 200444, Peoples R China
基金
中国国家自然科学基金;
关键词
AGRICULTURAL ROBOTS; ALGORITHM; AREAS;
D O I
10.1007/s10846-024-02073-8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Coverage path planning (CPP) is in great demand with applications in agriculture, mining, manufacturing, etc. Most research in this area focused on 2D CPP problems solving the coverage problem with irregular 2D maps. Comparatively, CPP on uneven terrains is not fully solved. When there are many slopy areas in the working field, it is necessary to adjust the path shape and make it adapt to the 3D terrain surface to save energy consumption. This article proposes a terrain-shape-adaptive CPP method with three significant features. First, the paths grow by themselves according to the local terrain surface shapes. Second, the growth rule utilizes the 3D terrain traversability analysis, which makes them automatically avoid entering hazardous zones. Third, the irregularly distributed paths are connected under an optimal sequence with an improved genetic algorithm. As a result, the method can provide an autonomously growing terrain-adaptive coverage path with high energy efficiency and coverage rate compared to previous research works. It is demonstrated on various maps and is proven to be robust to terrain conditions.
引用
收藏
页数:19
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