Demo Data from SIGIR 2026 / reviewers in the wild / expert
Harald Staab
dblp:11/7415
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2
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
2 papers |
Robot manipulation · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › dexterous manipulation
extrinsic dexterity |
0.4 | 2 | 2014 | Regrasping objects using extrinsic dexterity · ICRA 2014 Extrinsic dexterity: In-hand manipulation with external forces · ICRA 2014 |
Robotics › Robot manipulation › dexterous manipulation
in-hand manipulation |
0.4 | 2 | 2014 | Regrasping objects using extrinsic dexterity · ICRA 2014 Extrinsic dexterity: In-hand manipulation with external forces · ICRA 2014 |
Robotics › Robot manipulation › grasping
regrasping |
0.4 | 2 | 2014 | Regrasping objects using extrinsic dexterity · ICRA 2014 Extrinsic dexterity: In-hand manipulation with external forces · ICRA 2014 |
Robotics › Robot manipulation
grasping |
0.1 | 1 | 2014 | Extrinsic dexterity: In-hand manipulation with external forces · ICRA 2014 |
Methods — techniques the papers use, named apart from their topics
open-loop scripted actions · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Extrinsic dexterity: In-hand manipulation with external forcesabstract“In-hand manipulation” is the ability to reposition an object in the hand, for example when adjusting the grasp of a hammer before hammering a nail. The common approach to in-hand manipulation with robotic hands, known as dexterous manipulation [1], is to hold an object within the fingertips of the hand and wiggle the fingers, or walk them along the object's surface. Dexterous manipulation, however, is just one of the many techniques available to the robot. The robot can also roll the object in the hand by using gravity, or adjust the object's pose by pressing it against a surface, or if fast enough, it can even toss the object in the air and catch it in a different pose. All these techniques have one thing in common: they rely on resources extrinsic to the hand, either gravity, external contacts or dynamic arm motions. We refer to them as “extrinsic dexterity”. In this paper we study extrinsic dexterity in the context of regrasp operations, for example when switching from a power to a precision grasp, and we demonstrate that even simple grippers are capable of ample in-hand manipulation. We develop twelve regrasp actions, all open-loop and hand-scripted, and evaluate their effectiveness with over 1200 trials of regrasps and sequences of regrasps, for three different objects (see video [2]). The long-term goal of this work is to develop a general repertoire of these behaviors, and to understand how such a repertoire might eventually constitute a general-purpose in-hand manipulation capability. Nikhil Chavan Dafle, Alberto Rodriguez 0003, Robert Paolini, Bowei Tang, Siddhartha S. Srinivasa, Michael A. Erdmann, Matthew T. Mason, Ivan Lundberg, Harald Staab, Thomas A. Fuhlbrigge |
ICRA | 9 |
| 2014 | Regrasping objects using extrinsic dexterityabstractThis video presents the application of Extrinsic Dexterity to change the pose of an object in the hand, i.e., to regrasp the object. Nikhil Chavan Dafle, Alberto Rodriguez 0003, Robert Paolini, Bowei Tang, Siddhartha S. Srinivasa, Michael A. Erdmann, Matthew T. Mason, Ivan Lundberg, Harald Staab, Thomas A. Fuhlbrigge |
ICRA | 9 |