Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plants
Inspired by the phototropism of plants, a novel variant of the rapidly exploring random tree algorithm as called phototropism rapidly exploring random tree is proposed. The phototropism rapidly exploring random tree algorithm expands less tree nodes during the exploration period and has shorter path...
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Online Access: | https://doi.org/10.1177/1729881420945213 |
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doaj-a828e7cfa10c45eab1a6c31021ef16f62020-11-25T02:34:29ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142020-09-011710.1177/1729881420945213Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plantsChengchen Zhuge0Jiayin Liu1Dongyan Guo2Ying Cui3 Department of Computer Information and Cyber Security, , Nanjing, China Department of Computer Information and Cyber Security, , Nanjing, China College of Computer Science and Technology, , Hangzhou, Zhejiang, China College of Computer Science and Technology, , Hangzhou, Zhejiang, ChinaInspired by the phototropism of plants, a novel variant of the rapidly exploring random tree algorithm as called phototropism rapidly exploring random tree is proposed. The phototropism rapidly exploring random tree algorithm expands less tree nodes during the exploration period and has shorter path length than the original rapidly exploring random tree algorithm. In the algorithm, a virtual light source is set up at the goal point, and a light beam propagation method is adopted on the map to generate a map of light intensity distribution. The phototropism rapidly exploring random tree expands its node toward the space where the light intensity is higher, while the original rapidly exploring random tree expands its node based on the uniform sampling strategy. The performance of the phototropism rapidly exploring random tree is tested in three scenarios which include the simulation environment and the real-world environment. The experimental results show that the proposed phototropism rapidly exploring random tree algorithm has a higher sampling efficiency than the original rapidly exploring random tree, and the path length is close to the optimal solution of the rapidly exploring random tree* algorithm without considering the non-holonomic constraint.https://doi.org/10.1177/1729881420945213 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chengchen Zhuge Jiayin Liu Dongyan Guo Ying Cui |
spellingShingle |
Chengchen Zhuge Jiayin Liu Dongyan Guo Ying Cui Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plants International Journal of Advanced Robotic Systems |
author_facet |
Chengchen Zhuge Jiayin Liu Dongyan Guo Ying Cui |
author_sort |
Chengchen Zhuge |
title |
Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plants |
title_short |
Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plants |
title_full |
Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plants |
title_fullStr |
Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plants |
title_full_unstemmed |
Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plants |
title_sort |
phototropism rapidly exploring random tree: an efficient rapidly exploring random tree approach based on the phototropism of plants |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2020-09-01 |
description |
Inspired by the phototropism of plants, a novel variant of the rapidly exploring random tree algorithm as called phototropism rapidly exploring random tree is proposed. The phototropism rapidly exploring random tree algorithm expands less tree nodes during the exploration period and has shorter path length than the original rapidly exploring random tree algorithm. In the algorithm, a virtual light source is set up at the goal point, and a light beam propagation method is adopted on the map to generate a map of light intensity distribution. The phototropism rapidly exploring random tree expands its node toward the space where the light intensity is higher, while the original rapidly exploring random tree expands its node based on the uniform sampling strategy. The performance of the phototropism rapidly exploring random tree is tested in three scenarios which include the simulation environment and the real-world environment. The experimental results show that the proposed phototropism rapidly exploring random tree algorithm has a higher sampling efficiency than the original rapidly exploring random tree, and the path length is close to the optimal solution of the rapidly exploring random tree* algorithm without considering the non-holonomic constraint. |
url |
https://doi.org/10.1177/1729881420945213 |
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