Space robot teleoperation is an important technology in the space human-robot interaction and collaboration. Hand-based visual teleoperation can make the operation more natural and convenient. The fast and accuracy hand detection is one of the most difficult and important problem in the hand-based space robot teleoperation. In this work, we propose a fast and accurate hand detection method by using a spatial-channel attention single shot multibox detector (SCA-SSD). The SSD framework is used and improved in our method by introducing spatial-channel attentions with feature fusion. To increase the restricted receptive field in shallow layers, two shallow layers are fused with deep layers by using feature fusion modules. And spatial attention and channel-wise attention are also used to extract more efficient features. This method can not only ease the computational burden but also bring more contextual information. To evaluate the effectiveness of the proposed method, experiments on some public datasets and a custom astronaut hand detection dataset (AHD) are conducted. The results show that our method can improve the hand detection accuracy by 2.7% compared with the original SSD with only 15 fps speed drops. In addition, the space robot teleoperation experiment proves that our hand detection method can be well utilized in the space robot teleoperation system.

No abstract

No abstract

No abstract