Evidence map›Paper›PMID 38637556›Full record

ArticleScientific reports2024

Route planning of mobile robot based on improved RRT star and TEB algorithm.

Xiong Yin, Wentao Dong, Xiaoming Wang, Yongxiang Yu, Daojin Yao

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xiong YinSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330000, China.
Wentao DongSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330000, China.
Xiaoming WangSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330000, China.
Yongxiang YuSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330000, China.
Daojin YaoSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330000, China. ydaojin@whu.edu.cn.

Funding

Jiangxi Graduate Student Innovation Special Fund Project YC2023-S468Jiangxi Provincial Natural Science Foundation under Grants 20224BAB214051Jiangxi Provincial Natural Science Foundation under Grants 20232BAB214045Key R & D plan of Jiangxi Province under Grant 20212BBE51010National Natural Science Foundation of China under Grant 52165069National Natural Science Foundation of China under Grant 52365003Training Plan for Academic and Technical Leaders of Major Disciplines in Jiangxi Province under Grants 20232BCJ23027
6 · The paper itself

Abstract

This paper presents a fusion algorithm based on the enhanced RRT* TEB algorithm. The enhanced RRT* algorithm is utilized for generating an optimal global path. Firstly, proposing an adaptive sampling function and extending node bias to accelerate global path generation and mitigate local optimality. Secondly, eliminating path redundancy to minimize path length. Thirdly, imposing constraints on the turning angle of the path to enhance path smoothness. Conducting kinematic modeling of the mobile robot and optimizing the TEB algorithm to align the trajectory with the mobile robot's kinematics. The integration of these two algorithms culminates in the development of a fusion algorithm. Simulation and experimental results demonstrate that, in contrast to the traditional RRT* algorithm, the enhanced RRT* algorithm achieves a 5.8% reduction in path length and a 62.5% decrease in the number of turning points. Utilizing the fusion algorithm for path planning, the mobile robot generates a superior, seamlessly smooth global path, adept at circumventing obstacles. Furthermore, the local trajectory meticulously conforms to the kinematic constraints of the mobile robot.

Indexed as

AGVKinematicPath planningRRT* algorithmTEB algorithm

Identifiers

PMID38637556
PMCPMC11026392

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.