Demo Data from EDBT 2026 / reviewers in the wild / expert
Viviana Morlando
dblp:324/6283
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021
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 · 50% Legged, aerial and field robots · 25% Motion planning and robot control · 25% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots
legged robots |
0.6 | 1 | 2022 | Nonprehensile Object Transportation with a Legged Manipulator · ICRA 2022 |
Robotics › Robot manipulation
nonprehensile manipulation |
0.6 | 1 | 2022 | Nonprehensile Object Transportation with a Legged Manipulator · ICRA 2022 |
Robotics › Robot manipulation › object manipulation
object transport |
0.6 | 1 | 2022 | Nonprehensile Object Transportation with a Legged Manipulator · ICRA 2022 |
Robotics › Motion planning and robot control
whole-body control |
0.6 | 1 | 2022 | Nonprehensile Object Transportation with a Legged Manipulator · ICRA 2022 |
Methods — techniques the papers use, named apart from their topics
quadratic optimization · 0.6contact force control · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Nonprehensile Object Transportation with a Legged ManipulatorabstractThis paper tackles the problem of nonprehensile object transportation through a legged manipulator. A whole-body control architecture is devised to prevent sliding of the object placed on the tray at the manipulator's end-effector and retain the legged robot balance during walking. The controller solves a quadratic optimization problem to realize the sought transportation task while maintaining the contact forces between the tray and the object and between the legs and the ground within their respective friction cones, also considering limits on the input torques. An extensive simulation campaign confirmed the feasibility of the approach and evaluated the control performance through a thorough statistical analysis conducted varying mass, friction, and the dimension of the transported object. Viviana Morlando, Mario Selvaggio, Fabio Ruggiero |
ICRA | 1 |