Media Summary: Objects are indispensable tools in our daily lives. Recent research has demonstrated their potential to act as conduits for digital ... UC Berkeley AUTOLAB Dex-Net 2.0: Deep Learning to Plan Robust Roger Boldu, Alexandru Dancu, Denys J.C. Matthies, Pablo Gallego Cascón, Shanaka Ransir, and Suranga Nanayakkara. 2018.

Grasping Microgestures Video - Detailed Analysis & Overview

Objects are indispensable tools in our daily lives. Recent research has demonstrated their potential to act as conduits for digital ... UC Berkeley AUTOLAB Dex-Net 2.0: Deep Learning to Plan Robust Roger Boldu, Alexandru Dancu, Denys J.C. Matthies, Pablo Gallego Cascón, Shanaka Ransir, and Suranga Nanayakkara. 2018. GraspR: A Computational Model of Spatial User Preferences for Adaptive

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Grasping Microgestures Video
Grasping Microgestures: Eliciting Single-hand Microgestures for Handheld Objects
SoloFinger: Robust Microgestures while Grasping Everyday Objects
GraspUI: Seamlessly Integrating Object-Centric Gestures within the Seven Phases of Grasping
SoloFinger: Robust Microgestures while Grasping Everyday Objects
GraspUI: Seamlessly Integrating Object-Centric Gestures within the Seven Phases of Grasping [30 sec]
DexNet 2.0: 99% Precision Grasping
Thumb-In-Motion: Evaluating Thumb-to-Ring Microgestures for Athletic Activity
A Variable Palm-width Robot Hand Capable of Grasping a Wide Array of Object Geometries
GraspR: A Computational Model of Spatial User Preferences for Adaptive Grasp UI Design
Grasping
Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter | Presentation
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Grasping Microgestures Video

Grasping Microgestures Video

Single-hand

Grasping Microgestures: Eliciting Single-hand Microgestures for Handheld Objects

Grasping Microgestures: Eliciting Single-hand Microgestures for Handheld Objects

Grasping Microgestures

SoloFinger: Robust Microgestures while Grasping Everyday Objects

SoloFinger: Robust Microgestures while Grasping Everyday Objects

SoloFinger: Robust

GraspUI: Seamlessly Integrating Object-Centric Gestures within the Seven Phases of Grasping

GraspUI: Seamlessly Integrating Object-Centric Gestures within the Seven Phases of Grasping

Objects are indispensable tools in our daily lives. Recent research has demonstrated their potential to act as conduits for digital ...

SoloFinger: Robust Microgestures while Grasping Everyday Objects

SoloFinger: Robust Microgestures while Grasping Everyday Objects

SoloFinger: Robust

GraspUI: Seamlessly Integrating Object-Centric Gestures within the Seven Phases of Grasping [30 sec]

GraspUI: Seamlessly Integrating Object-Centric Gestures within the Seven Phases of Grasping [30 sec]

Objects are indispensable tools in our daily lives. Recent research has demonstrated their potential to act as conduits for digital ...

DexNet 2.0: 99% Precision Grasping

DexNet 2.0: 99% Precision Grasping

UC Berkeley AUTOLAB http://bit.ly/AUTOLAB Dex-Net 2.0: Deep Learning to Plan Robust

Thumb-In-Motion: Evaluating Thumb-to-Ring Microgestures for Athletic Activity

Thumb-In-Motion: Evaluating Thumb-to-Ring Microgestures for Athletic Activity

Roger Boldu, Alexandru Dancu, Denys J.C. Matthies, Pablo Gallego Cascón, Shanaka Ransir, and Suranga Nanayakkara. 2018.

A Variable Palm-width Robot Hand Capable of Grasping a Wide Array of Object Geometries

A Variable Palm-width Robot Hand Capable of Grasping a Wide Array of Object Geometries

Video

GraspR: A Computational Model of Spatial User Preferences for Adaptive Grasp UI Design

GraspR: A Computational Model of Spatial User Preferences for Adaptive Grasp UI Design

GraspR: A Computational Model of Spatial User Preferences for Adaptive

Grasping

Grasping

Example based-reaching with

Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter | Presentation

Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter | Presentation

Video

The GRASPS Model

The GRASPS Model

n this session, I explore how