LEARNING
Recognition of Environmental Impedance Configuration by Neural Network Using Time-Series Contact State Response
Kazuki Yane, Takahiro Nozaki
- 发表年份
- 2022
- 引用次数
- 9
摘要
There is a need to use robots in a variety of environments. If the environment can be recognized, it will be possible to generate appropriate motions and judge the situation. The image-based environment recognition does not provide physical information such as the impedance of the target object. This paper proposes a method to recognize the configuration of objects by touching them before performing actions. By conducting simulations, the results of the recognition with a neural network (NN) using time-series data of the action were verified.
关键词
Computer scienceArtificial neural networkRobotArtificial intelligenceObject (grammar)Action (physics)Cognitive neuroscience of visual object recognitionElectrical impedanceVariety (cybernetics)Series (stratigraphy)
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