In this paper new grasp quality measures considering both object dynamics and pose uncertainty are proposed. Dynamics of the object is incorporated into our grasping simulation to capture the change of its pose and contact points during grasping. Pose uncertainty is considered by running multiple simulations starting from slightly different initial poses sampled from a probability distribution model. A simple robotic grasping strategy is simulated and the quality score of the resulting grasp is evaluated from the simulation result. The effectiveness of the new quality measures on predicting the actual grasp success rate is shown through a real robot experiment.</p
International audienceRobotic grasping is very sensitive to how accurate is the pose estimation of t...
Underactuated and synergy-driven hands are gaining attention in the grasping community mainly due to...
This paper presents an experimental framework to quantify grasp compliance, especially at object bou...
<p>In this paper new grasp quality measures considering both object dynamics and pose uncertainty ar...
Robot grasp quality metrics are used to evaluate, compare and select robotic grasp configurations. M...
We propose a new approach to investigate and quantify dynamic grasp performance. Oftentimes, existin...
This paper focuses on the problem of grasp stability and grasp quality analysis. An elegant way to e...
The correct grasp of objects is a key aspect for the right fulfillment of a given task. In robotics,...
There is a lack of quality indexes to evaluate grasps that are more likely to allow a hand-to-hand t...
In this paper, the problem of learning grasp stability in robotic object grasping based on tactile m...
This paper presents an integration of grasp planning and online grasp stability assessment based on ...
Performing a grasp is a pivotal capability for a robotic gripper. We propose a new evaluation approa...
Robot grasp planning has been extensively studied in the last decades often consisting of two differ...
Roa M, Kõiva R, Castellini C. Experimental Evaluation of Human Grasps Using a Sensorized Object. Pre...
This paper addresses a new approach to the problem of selecting contact locations for grasping in th...
International audienceRobotic grasping is very sensitive to how accurate is the pose estimation of t...
Underactuated and synergy-driven hands are gaining attention in the grasping community mainly due to...
This paper presents an experimental framework to quantify grasp compliance, especially at object bou...
<p>In this paper new grasp quality measures considering both object dynamics and pose uncertainty ar...
Robot grasp quality metrics are used to evaluate, compare and select robotic grasp configurations. M...
We propose a new approach to investigate and quantify dynamic grasp performance. Oftentimes, existin...
This paper focuses on the problem of grasp stability and grasp quality analysis. An elegant way to e...
The correct grasp of objects is a key aspect for the right fulfillment of a given task. In robotics,...
There is a lack of quality indexes to evaluate grasps that are more likely to allow a hand-to-hand t...
In this paper, the problem of learning grasp stability in robotic object grasping based on tactile m...
This paper presents an integration of grasp planning and online grasp stability assessment based on ...
Performing a grasp is a pivotal capability for a robotic gripper. We propose a new evaluation approa...
Robot grasp planning has been extensively studied in the last decades often consisting of two differ...
Roa M, Kõiva R, Castellini C. Experimental Evaluation of Human Grasps Using a Sensorized Object. Pre...
This paper addresses a new approach to the problem of selecting contact locations for grasping in th...
International audienceRobotic grasping is very sensitive to how accurate is the pose estimation of t...
Underactuated and synergy-driven hands are gaining attention in the grasping community mainly due to...
This paper presents an experimental framework to quantify grasp compliance, especially at object bou...