Sensory-Motor Learning for Simultaneous Control of Motion and Force: Generating Rubbing Motion against Uneven Object

Hiroshi Ito, Takumi Kurata,Tetsuya Ogata

2022 IEEE/SICE International Symposium on System Integration (SII)(2022)

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摘要
We propose a motion generation model for simultaneous control of motion and force using deep learning. Conventional force control methods require expensive torque sensors and complex control theory, and implementing force control for each task requires huge development costs. In this paper, we realize rubbing motions against an uneven object at low cost by using a motion generation method that tak...
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关键词
Costs,Torque,Force,Predictive models,Feature extraction,Robot sensing systems,Sensors
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