A visual terrain classification method for mobile robots' navigation based on convolutional neural network and support vector machine.
Wanli WangBotao ZhangKaiqi WuSergey A. ChepinskiyAnton A. ZhilenkovSergei G. ChernyiAleksandr Y. KrasnovPublished in: Trans. Inst. Meas. Control (2022)
Keyphrases
- classification method
- support vector machine
- mobile robot
- convolutional neural network
- outdoor environments
- obstacle avoidance
- indoor environments
- autonomous navigation
- support vector machine svm
- unknown environments
- rough terrain
- knn
- k nearest neighbor
- path planning
- face detection
- svm classifier
- classification algorithm
- classification scheme
- text classification
- dynamic environments
- autonomous robots
- feature vectors
- training data
- support vector
- visual features
- machine learning
- svm classification
- object detection
- selected features
- motion planning
- bayesian networks
- nearest neighbor rule
- image processing
- neural network
- small number
- collision free
- kernel function
- collision avoidance
- kernel methods
- pairwise
- feature selection
- data mining
- real world