Demo Data from EDBT 2026 / reviewers in the wild / expert
Sinan Emre
dblp:246/1060
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 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 |
Legged, aerial and field robots · 91% Robot manipulation · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots › legged robots
legged robot locomotion |
0.8 | 1 | 2024 | Introducing the Carpal-Claw: a Mechanism to Enhance High-Obstacle Negotiation for Quadruped Robots · ICRA 2024 |
Robotics › Legged, aerial and field robots › rough terrain locomotion
obstacle traversal |
0.8 | 1 | 2024 | Introducing the Carpal-Claw: a Mechanism to Enhance High-Obstacle Negotiation for Quadruped Robots · ICRA 2024 |
Robotics › Legged, aerial and field robots › legged robots › legged robot locomotion
quadruped locomotion |
0.8 | 1 | 2024 | Introducing the Carpal-Claw: a Mechanism to Enhance High-Obstacle Negotiation for Quadruped Robots · ICRA 2024 |
Robotics › Robot manipulation › robot design
mechanism design |
0.2 | 1 | 2024 | Introducing the Carpal-Claw: a Mechanism to Enhance High-Obstacle Negotiation for Quadruped Robots · ICRA 2024 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Introducing the Carpal-Claw: a Mechanism to Enhance High-Obstacle Negotiation for Quadruped RobotsabstractThe capability of a quadruped robot to negotiate obstacles is tightly connected to its leg workspace and joint torque limits. When facing terrain where the height of obstacles is close to the leg length, the locomotion robustness and safety are reduced since more dynamic motions are required to traverse it. In this paper, we introduce a new mechanism called the Carpal-Claw, which enables quadruped robots to negotiate higher obstacles and adds safety to the locomotion by allowing the robot to negotiate obstacles under static and quasi-static locomotion and regular joint torque demands. The design of the mechanism is detailed, as well as the methodology to exploit the mechanism in the locomotion control framework. The Carpal-Claw functionality is validated through various experiments on a very high obstacle and stairs-like terrains using an Aliengo robot. We demonstrate how Aliengo can safely descend a step height of 40cm, which is 80% of its leg length. To the best knowledge of the authors, this is the first time a mechanism like the C-Claw is proposed for improving quadruped robot locomotion over high obstacles. Victor Barasuol, Sinan Emre, Vivian Suzano Medeiros, Angelo Bratta, Claudio Semini |
ICRA | 2 |