The above pipeline abstracts the grasping location selection task from the main process of grasp generation, which lowers the learning difficulty while avoiding the performance degradation problem of deep graph networks. The established pipeline is evaluated on the GraspNet-1Billion dataset, demonstrating ...
Although humans can instinctively execute grasps in an accurate, stable, and rapid way even under a constantly changing environment, intelligent grasping remains a challenging task for robots. As a prerequisite for grasping, robots need to correctly identify the best grasping location of unknown ...
robotic perception problems are often used in closed loop with controllers, so there are stringent requirements on performance and computational speed. In the past, hand-designing features has been the most popular method for several robotic tasks, ...
Each data sample provided was associated to an accurate timestamp using Windows performance counters. The number and corresponding position of each Cyberglove sensor is shown in Fig. 1. The acquisition setup is described in detail in [27, 28]. Fig. 1 a Cyberglove II device. b The number ...
Recognizing human hand grasp movements through surface electromyogram (sEMG) is a challenging task. In this paper, we investigated nonlinear measures based on recurrence plot, as a tool to evaluate the hidden dynamical characteristics of sEMG during four different hand moveme...
of neurons without relying on any assumptions about what the brain is trying to do. The patterns can be distinguished based on differences in their activity and can cluster together based on their similarities without the researchers imposing their own view of events going on in the task. ...