Open AccessAdaptive online terrain classification method for mobile robot based on vibration signals
Author(s) -
Mingming Wang,
YE Liming,
Xiaoyun Sun
Publication year - 2021
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.1177/17298814211062035
Subject(s) - computer science , terrain , vibration , artificial intelligence , robot , mobile robot , signal (programming language) , interference (communication) , computer vision , support vector machine , frequency domain , pattern recognition (psychology) , acoustics , channel (broadcasting) , telecommunications , ecology , physics , biology , programming language
To improve the accuracy of terrain classification during mobile robot operation, an adaptive online terrain classification method based on vibration signals is proposed. First, the time domain and the combined features of the time, frequency, and time–frequency domains in the original vibration signal are extracted. These are adopted as the input of the random forest algorithm to generate classification models with different dimensions. Then, by judging the relationship between the current speed of the mobile robot and its critical speed, the classification model of different dimensions is adaptively selected for online classification. Offline and online experiments are conducted for four different terrains. The experimental results show that the proposed method can effectively avoid the self-vibration interference caused by an increase in the robot’s moving speed and achieve higher terrain classification accuracy.