Open AccessResearch on optimization of complex path of inspection robot
Author(s) -
Dongyang Li,
Zhifeng Zhong,
Tianxiong Chen,
Qiangqiang Yan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2029/1/012124
Subject(s) - robot , merge (version control) , motion planning , computer science , mobile robot , grid reference , grid , tracing , robotics , matlab , artificial intelligence , key (lock) , convergence (economics) , path (computing) , real time computing , simulation , computer vision , mathematics , geometry , computer security , programming language , economics , information retrieval , economic growth , operating system
It is a common method to use intelligent robots for automatic inspection in highly automated ships. Path planning and optimization research are an important part of robotics. Intelligent tracking is the key to autonomous movement of mobile robots. In this paper, a grid map is used to establish a simulation model of the robot tracing environment. In a grid map, the more complex the map environment, the slower the algorithm will converge. The -fill-merge method processes the concave obstacles in the environment into regular shapes, reduces the number of unnecessary calculations, thereby greatly optimizing the tracing environment and speeding up the convergence speed. Finally, the MATLAB simulation experiment shows that the method based on environment optimization can effectively accelerate the convergence speed, avoid the local optimum, and quickly find the global optimum when dealing with the problem of autonomous tracking of intelligent robots in a map environment with a large number of concave obstacles. solution.