4 accepted papers
The precise identification of the robot curtain wall assembly state is crucial for improving construction efficiency. Traditional methods remain sensitive to noise in high-dimensional sensor data and require extensive datasets, resulting in limited generalization. A method for identifying the robot
The proficiency of robots in cloth manipulation is crucial for their potential widespread deployment in household service contexts, with the task of unfolding cloth being particularly indispensable. Unlike rigid objects, cloth has a high-dimensional state space, which poses significant challenges fo
Snap-fit recognition is an essential capability for industrial robots in manufacturing. The goal is to protect fragile parts by quickly detecting snap-fit signals in the assembly. In this letter, we propose a fast recognition method of snap-fit for industrial robots. A snap-fit dataset generation st
Deformable object manipulation has been considered a challenging task for robots for its complex dynamics and the infinite dimensional configuration space. Fabric unfolding manipulation takes on critical significance in the textile industry and household services. Accordingly, enabling robots to pos