Autonomous Navigation of Robots Based on the Improved Informed-RRT∗ Algorithm and DWA

An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT∗ algorithm in robot autonomous navigation. First, the greedy algorithm is introduced in the path planning procedure. When a new node is obtained, it will...

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Published inJournal of Robotics Vol. 2022; pp. 1 - 9
Main Authors Dai, Jun, Li, Dongfang, Zhao, Junwei, Li, Yanqin
Format Journal Article
LanguageEnglish
Published New York Hindawi 08.02.2022
John Wiley & Sons, Inc
Wiley
Subjects
Algorithms
Autonomous navigation
Efficiency
Greedy algorithms
Nodes
Optimization
Path planning
Robotics industry
Robots
Online AccessGet full text
ISSN1687-9600
1687-9619
DOI10.1155/2022/3477265

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Abstract An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT∗ algorithm in robot autonomous navigation. First, the greedy algorithm is introduced in the path planning procedure. When a new node is obtained, it will be judged whether it can directly reach the target point. Second, the search scope of the potential optimal parent node becomes the constructed path, instead of the node tree, which reduces the number of nodes to be searched and improves the navigation efficiency. Combined with the dynamic window approach (DWA), the improved algorithm is utilized to simulate the autonomous navigation process of the robot based on the Robot Operating System (ROS) platform. The simulation results show that compared with the original algorithm, the length of the global path is reduced by 5.15%, and the time of planning path and autonomous navigation is shortened by 78.34% and 21.67%, respectively.
AbstractList An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT ∗ algorithm in robot autonomous navigation. First, the greedy algorithm is introduced in the path planning procedure. When a new node is obtained, it will be judged whether it can directly reach the target point. Second, the search scope of the potential optimal parent node becomes the constructed path, instead of the node tree, which reduces the number of nodes to be searched and improves the navigation efficiency. Combined with the dynamic window approach (DWA), the improved algorithm is utilized to simulate the autonomous navigation process of the robot based on the Robot Operating System (ROS) platform. The simulation results show that compared with the original algorithm, the length of the global path is reduced by 5.15%, and the time of planning path and autonomous navigation is shortened by 78.34% and 21.67%, respectively.
An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT[sup.∗] algorithm in robot autonomous navigation. First, the greedy algorithm is introduced in the path planning procedure. When a new node is obtained, it will be judged whether it can directly reach the target point. Second, the search scope of the potential optimal parent node becomes the constructed path, instead of the node tree, which reduces the number of nodes to be searched and improves the navigation efficiency. Combined with the dynamic window approach (DWA), the improved algorithm is utilized to simulate the autonomous navigation process of the robot based on the Robot Operating System (ROS) platform. The simulation results show that compared with the original algorithm, the length of the global path is reduced by 5.15%, and the time of planning path and autonomous navigation is shortened by 78.34% and 21.67%, respectively.
An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT∗ algorithm in robot autonomous navigation. First, the greedy algorithm is introduced in the path planning procedure. When a new node is obtained, it will be judged whether it can directly reach the target point. Second, the search scope of the potential optimal parent node becomes the constructed path, instead of the node tree, which reduces the number of nodes to be searched and improves the navigation efficiency. Combined with the dynamic window approach (DWA), the improved algorithm is utilized to simulate the autonomous navigation process of the robot based on the Robot Operating System (ROS) platform. The simulation results show that compared with the original algorithm, the length of the global path is reduced by 5.15%, and the time of planning path and autonomous navigation is shortened by 78.34% and 21.67%, respectively.
Audience Academic
Author Li, Dongfang
Zhao, Junwei
Li, Yanqin
Dai, Jun
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Snippet An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT∗ algorithm in...
An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT ∗ algorithm...
An improved method is proposed in this investigation to solve the problems of poor path quality and low navigation efficiency of the Informed-RRT[sup.∗]...
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SubjectTerms Algorithms
Autonomous navigation
Efficiency
Greedy algorithms
Nodes
Optimization
Path planning
Robotics industry
Robots
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Title Autonomous Navigation of Robots Based on the Improved Informed-RRT∗ Algorithm and DWA
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