4 accepted papers
Visual servoing is fundamental to robotic applications, enabling precise positioning and control. However, applying it to textureless objects remains a challenge due to the absence of reliable visual features. Moreover, adverse visual conditions, such as occlusions, often corrupt visual feedback, le…
Depth from focus (DFF) is a well-established method for measuring depth in vision systems. However, its efficacy and accuracy are limited by the slow speed required to capture high-quality focal stacks. We address this limitation by leveraging emerging hardware technologies: the event camera and liq
6D pose estimation of textureless objects is a valuable but challenging task for many robotic applications. In this work, we propose a framework to address this challenge using only RGB images acquired from multiple viewpoints. The core idea of our approach is to decouple 6D pose estimation into a s…
As human-assisting robots are starting to play an important role in the food service and hospitality field, service vision for robot manipulation on intra-category objects, which have variations in shape, size, and appearance, is an inevitable and valuable task. Previous works typically rely on esti