LEARNING
Human Action Imitation System Based on Nao Robot
Ning Hu, Lin Zheng
- 发表年份
- 2019
- 引用次数
- 2
摘要
A human action imitation system based on Nao robot is proposed in this paper. A new strategy, combining Momentum with Stochastic gradient descent(SGD), is designed to accelerate the training process of Convolutional Neural Networks(CNN). The CNN is used to recognize the 2D coordinate of joints of a human body. This data is translate to Nao Robot and make it to imitate human action. The experiments show that the training rate is faster than traditional training method. The Robot can imitate the human action accurately.
关键词
Artificial intelligenceComputer scienceAction (physics)RobotImitationConvolutional neural networkStochastic gradient descentProcess (computing)Human–robot interactionComputer vision
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