For humans, the process of grasping an object relies heavily on rich tactile feedback. Most recent robotic grasping work, however, has been based only on visual input, and thus cannot easily benefit from feedback after initiating contact. In this letter, we investigate how a robot can learn to use tactile information to iteratively and efficiently adjust its grasp. To this end, we propose an end-to-end action-conditional model that learns regrasping policies from raw visuo-tactile data. This model - a deep, multimodal convolutional network - predicts the outcome of a candidate grasp adjustment, and then executes a grasp by iteratively selecting the most promising actions. Our approach requires neither calibration of the tactile sensors nor ...
A robot’s ability to grasp moving objects depends on the availability of real-time sensor data in bo...
Perceiving and manipulating deformable objects with the sense of touch are essential skills in every...
Abstract — To perform robust grasping, a multi-fingered robotic hand should be able to adapt its gra...
This paper presents a novel regrasp control policy that makes use of tactile sensing to plan local g...
The purpose of this project is to find how to extract valuable information and applications of a tac...
Currently, robots display manipulation capabilities that translate into actions such as picking and ...
Our aim is to predict the stability of a grasp from the perceptions available to a robot before atte...
In the context of robotic object manipulation, this work presents a simple regrasp policy based on t...
In the context of robotic object manipulation, this work presents a simple regrasp policy based on t...
In the context of robotic object manipulation, this work presents a simple regrasp policy based on t...
Humans learn by interacting with their surroundings using all of their senses. The first of these se...
We still struggle to deliver autonomous robots that perform manipulation tasks as simple for a human...
The soft fingers and strategic grasping skills enable the human hands to grasp objects in a stable m...
The soft fingers and strategic grasping skills enable the human hands to grasp objects in a stable m...
In the context of object interaction and manipulation, one characteristic of a robust grasp is its a...
A robot’s ability to grasp moving objects depends on the availability of real-time sensor data in bo...
Perceiving and manipulating deformable objects with the sense of touch are essential skills in every...
Abstract — To perform robust grasping, a multi-fingered robotic hand should be able to adapt its gra...
This paper presents a novel regrasp control policy that makes use of tactile sensing to plan local g...
The purpose of this project is to find how to extract valuable information and applications of a tac...
Currently, robots display manipulation capabilities that translate into actions such as picking and ...
Our aim is to predict the stability of a grasp from the perceptions available to a robot before atte...
In the context of robotic object manipulation, this work presents a simple regrasp policy based on t...
In the context of robotic object manipulation, this work presents a simple regrasp policy based on t...
In the context of robotic object manipulation, this work presents a simple regrasp policy based on t...
Humans learn by interacting with their surroundings using all of their senses. The first of these se...
We still struggle to deliver autonomous robots that perform manipulation tasks as simple for a human...
The soft fingers and strategic grasping skills enable the human hands to grasp objects in a stable m...
The soft fingers and strategic grasping skills enable the human hands to grasp objects in a stable m...
In the context of object interaction and manipulation, one characteristic of a robust grasp is its a...
A robot’s ability to grasp moving objects depends on the availability of real-time sensor data in bo...
Perceiving and manipulating deformable objects with the sense of touch are essential skills in every...
Abstract — To perform robust grasping, a multi-fingered robotic hand should be able to adapt its gra...