Improvement of Gmapping Algorithm Based on Non-continuous System
Tianshu Zheng, Chongxi Meng, Peng Zou, Jiao Wang · 2019
With the development of science and technology, robots are gradually replacing simple human labor and become an indispensable part of life. In the process of grain transportation in the granary, we use the robot as the tools, whereas, there are a lot of non-continuous environments, which pose a challenge to the construction of real-time map for robots. In this paper, we propose a modeling of a noncontinuous environment based on Gazebo platform. Then we raise a modified algorithm according to the Markov chain. By building the model of non-continuous environments in Gazebo platform, the effectiveness of the model is verified by comparing the model of plane and slope. According to this, we can solve the problem of hard to obtain accurate data from the real-world scenario to modify algorithms, and the efficiency is greatly improved.