Back to Search Start Over

RRT Autonomous Detection Algorithm Based on Multiple Pilot Point Bias Strategy and Karto SLAM Algorithm.

Authors :
Lieping Zhang
Xiaoxu Shi
Liu Tang
Yilin Wang
Jiansheng Peng
Jianchu Zou
Source :
Computers, Materials & Continua; 2024, Vol. 78 Issue 2, p2111-2136, 26p
Publication Year :
2024

Abstract

A Rapid-exploration Random Tree (RRT) autonomous detection algorithm based on the multi-guide-node deflection strategy andKarto Simultaneous Localization andMapping (SLAM) algorithmwas proposed to solve the problems of low efficiency of detecting frontier boundary points and drift distortion in the process of map building in the traditional RRT algorithm in the autonomous detection strategy of mobile robot. Firstly, an RRT global frontier boundary point detection algorithm based on the multi-guide-node deflection strategy was put forward, which introduces the reference value of guide nodes' deflection probability into the random sampling function so that the global search tree can detect frontier boundary points towards the guide nodes according to random probability. After that, a new autonomous detection algorithm for mobile robots was proposed by combining the graph optimization-based Karto SLAM algorithm with the previously improved RRT algorithm. The algorithm simulation platform based on the Gazebo platform was built. The simulation results show that compared with the traditional RRT algorithm, the proposed RRT autonomous detection algorithm can effectively reduce the time of autonomous detection, plan the length of detection trajectory under the condition of high average detection coverage, and complete the task of autonomous detection mapping more efficiently. Finally, with the help of the ROS-based mobile robot experimental platform, the performance of the proposed algorithm was verified in the real environment of different obstacles. The experimental results show that in the actual environment of simple and complex obstacles, the proposed RRT autonomous detection algorithm was superior to the traditional RRT autonomous detection algorithm in the time of detection, length of detection trajectory, and average coverage, thus improving the efficiency and accuracy of autonomous detection. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15462218
Volume :
78
Issue :
2
Database :
Complementary Index
Journal :
Computers, Materials & Continua
Publication Type :
Academic Journal
Accession number :
175815008
Full Text :
https://doi.org/10.32604/cmc.2024.047235