5 accepted papers
Transparent objects are common in industrial automation and daily life. However, accurate visual perception of these objects remains challenging due to their reflective and refractive properties. Most previous studies fail to capture contextual information or typically rely on regression-based metho
For humans, dense bin packing heavily relies on force perception. However, current robotic packing studies only focus on the visual input or adopt auxiliary push-to-place actions to eliminate gaps, suffering from high time expenditure and poor robustness. To address such limitations, we first introd…
The 6D pose estimation for metal parts is essential in industrial robotic applications. The color homogeneity, texture-less and light-reflecting properties of metal parts raise great challenges. Current 6D pose estimation methods have gained extensive concern using CNNs. However, these CNN-based met
High-precision robotic grasping is necessary for extensive grasping applications in the future. Most previous grasp detection methods fail to pay enough attention to learn grasp-related features and the detection accuracy is limited. In this letter, a novel attention-augmented grasp detection networ
Extensive research has been conducted on assessing grasp stability, a crucial prerequisite for achieving optimal grasping strategies, including the minimum force grasping policy. However, existing works employ basic feature-level fusion techniques to combine visual and tactile modalities, resulting…