Deep learning-based human motion recognition for predictive context-aware human-robot collaboration
0 摘要 智能製造領域中，提高人機協作（HRC）的運營效率和安全性的關鍵是人類操作員和機器人之間實時的情境感知（context awareness）。通過對人類操作員的行爲分析，可以提高情境感知的準確性和可靠性。爲實現這一目標，本文利用深度學習技術，進行連續人體行爲分析和HRC需求預測，從而改進機器人計劃和控制，共同完成任務。 我們提出的方法運動到發動機裝配的案例中，驗證了可行性。 1 引
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相關文章
- 1. Deep Visual Foresight for Planning Robot Motion
- 2. 論文：3D Convolutional Neural Networks for Human Action Recognition
- 3. CVPR 2017 Deep representation learning for human motion prediction and classification 論文解讀
- 4. Self-Attention Network for Skeleton-based Human Action Recognition
- 5. Deep learning for sensor-based human activity recognition: overview, challenges and opportunities
- 6. 論文筆記：Deep Convolutional Neural Network On Multichannel Time Series For Human Activity Recognition
- 7. 論文學習：Deep Convolutional Neural Networks On Multichannel Time Series For Human Activity Recognition
- 8. Deep High-Resolution Representation Learning for Human Pose Estimation
- 9. Deep Covariance Descriptors for Facial Expression Recognition
- 10. ResNet--Deep Residual Learning for Image Recognition