A goal-driven modular neural network predicts parietofrontal neural dynamics during grasping
نویسندگان
چکیده
منابع مشابه
Robotic Grasping: A Generic Neural Network Architecture
Reproducing human dexterity and flexibility in unknown environments is one of the major challenges of robotics. Among the issues related to the use of robots with artificial hands of varying complexity, the definition of their kinematical configuration when grasping an object is one of the most difficult problems. Indeed, it necessitates the consideration of a large number of constraints relate...
متن کاملAssociating Grasping with Convolutional Neural Network Features
In this work, we provide a solution for posturing the anthropomorphic Robonaut-2 hand and arm for grasping based on visual information. A mapping from visual features extracted from a convolutional neural network (CNN) to grasp points is learned. We demonstrate that a CNN pre-trained for image classification can be applied to a grasping task based on a small set of grasping examples. Our approa...
متن کاملParietofrontal integrity determines neural modulation associated with grasping imagery after stroke.
Chronic stroke patients with heterogeneous lesions, but no direct damage to the primary sensorimotor cortex, are capable of longitudinally acquiring the ability to modulate sensorimotor rhythms using grasping imagery of the affected hand. Volitional modulation of neural activity can be used to drive grasping functions of the paralyzed hand through a brain-computer interface. The neural substrat...
متن کاملA Planning Modular Neural-network Robot for Asynchronous Multi-goal Navigation Tasks
This paper focuses on two planning neural-network controllers, a "forward planner" and a "bidirectional planner". These have been developed within the framework of Sutton's Dyna-PI architectures (planning within reinforcement learning) and have already been presented in previous papers. The novelty of this paper is that the architecture of these planners is made modular in some of its component...
متن کاملA neural network interface to the DIGITS Grasping System
A neural network-based interface between an operator and the DIGITS Grasping System is proposed, and the initial results of the network training are presented. The neural network is responsible for accepting the description of an object to be held in a power grasp and mapping this data into a set of actuator torques which will allow DIGITS to rmly grasp the object. In addition, the network shou...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the National Academy of Sciences
سال: 2020
ISSN: 0027-8424,1091-6490
DOI: 10.1073/pnas.2005087117