Towards Human-in-the-Loop Shared Control for Upper-Limb Prostheses: A Systematic Analysis of State-of-the-Art Technologies
Dexterous prosthetic hand is an essential rehabilitation assistant device to improve the life
quality of amputee patients. Despite the continuous emergence of commercial prostheses …
quality of amputee patients. Despite the continuous emergence of commercial prostheses …
From pixels to percepts: Highly robust edge perception and contour following using deep learning and an optical biomimetic tactile sensor
Deep learning has the potential to have same the impact on robot touch as it has had on
robot vision. Optical tactile sensors act as a bridge between the subjects by allowing …
robot vision. Optical tactile sensors act as a bridge between the subjects by allowing …
Digital twin-enabled grasp outcomes assessment for unknown objects using visual-tactile fusion perception
Humans can instinctively predict whether a given grasp will be successful through visual
and rich haptic feedback. Towards the next generation of smart robotic manufacturing …
and rich haptic feedback. Towards the next generation of smart robotic manufacturing …
Mat: Multi-fingered adaptive tactile grasping via deep reinforcement learning
Vision-based grasping systems typically adopt an open-loop execution of a planned grasp.
This policy can fail due to many reasons, including ubiquitous calibration error. Recovery …
This policy can fail due to many reasons, including ubiquitous calibration error. Recovery …
A comprehensive review of robot intelligent grasping based on tactile perception
T Li, Y Yan, C Yu, J An, Y Wang, G Chen - Robotics and Computer …, 2024 - Elsevier
The Advancements in tactile sensors and machine learning techniques open new
opportunities for achieving intelligent grasping in robotics. Traditional robot is limited in its …
opportunities for achieving intelligent grasping in robotics. Traditional robot is limited in its …
Grasp state assessment of deformable objects using visual-tactile fusion perception
Humans can quickly determine the force required to grasp a deformable object to prevent its
sliding or excessive deformation through vision and touch, which is still a challenging task …
sliding or excessive deformation through vision and touch, which is still a challenging task …
Tactilegcn: A graph convolutional network for predicting grasp stability with tactile sensors
A Garcia-Garcia, BS Zapata-Impata… - … Joint Conference on …, 2019 - ieeexplore.ieee.org
Tactile sensors provide useful contact data during the interaction with an object which can
be used to accurately learn to determine the stability of a grasp. Most of the works in the …
be used to accurately learn to determine the stability of a grasp. Most of the works in the …
Improving grasp stability with rotation measurement from tactile sensing
Rotational displacement about the grasping point is a common grasp failure when an object
is grasped at a location away from its center of gravity. Tactile sensors with soft surfaces …
is grasped at a location away from its center of gravity. Tactile sensors with soft surfaces …
Genetic algorithm-based ensemble hybrid sparse ELM for grasp stability recognition with multimodal tactile signals
Grasp stability recognition based on tactile perception has attracted increasing attention in
the robotics community. In this article, we extract tactile features from multimodal tactile …
the robotics community. In this article, we extract tactile features from multimodal tactile …
Touch modality classification using recurrent neural networks
Recurrent Neural Networks (RNNs) are mainly designed to deal with sequence prediction
problems and they show their effectiveness in processing data originally represented as …
problems and they show their effectiveness in processing data originally represented as …