Zhongyao Zhang

dblp:203/4677 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
contact modeling
0.312017
Grasping posture estimation for a two-finger parallel gripper with soft material jaws using a curved contact area friction model · ICRA 2017
Robotics › Robot manipulation
grasping
0.312017
Grasping posture estimation for a two-finger parallel gripper with soft material jaws using a curved contact area friction model · ICRA 2017
Robotics › Robot manipulation › grasping
grasp quality evaluation
0.112017
Grasping posture estimation for a two-finger parallel gripper with soft material jaws using a curved contact area friction model · ICRA 2017

Methods — techniques the papers use, named apart from their topics

limit surface fitting · 0.3finite element method · 0.3
YearPublicationVenuePosition
2017 Grasping posture estimation for a two-finger parallel gripper with soft material jaws using a curved contact area friction model
abstract
We present a friction model for the curved contact area between a deformable object and soft parallel gripper jaws for grasping posture estimation. We show that the assumption of a planar contact area leads to an overestimation of the frictional force and torque, which might cause the object to slip. We simulate the contact with the Finite Element Method, then compute the friction wrenches, which are fitted with two limit surface models: an ellipsoid and a convex 4th-order polynomial. Despite a slightly higher fitting error, the ellipsoid limit surface is chosen to compute the grasp quality because of its simplicity. We compare the limit surfaces of our friction model with the planar contact model and show the improved accuracy obtainable with our model. We then apply the presented model for grasping posture estimation by simulating the contact for all grasp candidates. We show a grasp quality map (quality of all grasp candidates) and the best possible grasp location for several deformable objects.
Nicolas Alt, Zhongyao Zhang, Eckehard G. Steinbach
ICRA3