3D Virtual Activation Volume for Automated Grasping in Teleoperated Robotic Manipulation

This research study proposes a new method to improve robotic teleoperation during grasping tasks. In particular, the target is to reduce the operator's mental burden in grasping tasks, ensuring that the robotic grasping task is simplified for the operator. This simplification aims to improve the task grasping execution time and, in the meantime, increase its grasping success rate. The method is based on an adaptive 3D Virtual Activation Volume (VaV), which acts as a dynamic constraint to support the operator in the grasping task. This volume is centered around the object to grasp, and leverages advanced 3D modeling and active control techniques by using machine learning algorithms. In conclusion, the experimental results demonstrate that the proposed method enhances the precision of Human-Robot Interaction (HRI), resulting in a more intuitive teleoperation experience, with a 24% decrease in grasping execution time and a 26.4% increase in grasping success rate.