Demo Data from VLDB 2026 / reviewers in the wild / expert
Merlin Morlock
dblp:353/5931
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved
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 |
Robot manipulation · 70% Motion planning and robot control · 30% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control
collision detection |
0.7 | 1 | 2023 | Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot · ICRA 2023 |
Robotics › Robot manipulation › tactile sensing › contact sensing
contact localization |
0.7 | 1 | 2023 | Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot · ICRA 2023 |
Robotics › Robot manipulation
physical human-robot interaction |
0.7 | 1 | 2023 | Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot · ICRA 2023 |
Robotics › Robot manipulation › industrial robot
collaborative robot |
0.2 | 1 | 2023 | Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot · ICRA 2023 |
Methods — techniques the papers use, named apart from their topics
particle filter · 0.7generalized momentum observer · 0.7energy monitoring · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a CobotabstractIn physical human-robot interaction (pHRI) it is essential to reliably estimate and localize contact forces between the robot and the environment. In this paper, a complete contact detection, isolation, and reaction scheme is presented and tested on a new 6-dof industrial collaborative robot. We combine two popular methods, based on monitoring energy and generalized momentum, to detect and isolate collisions on the whole robot body in a more robust way. The experimental results show the effectiveness of our implementation on the LARA 5 cobot, that only relies on motor current and joint encoder measurements. For validation purposes, contact forces are also measured using an external GTE CoboSafe sensor. After a successful collision detection, the contact point location is isolated using a combination of the residual method based on the generalized momentum with a contact particle filter (CPF) scheme. We show for the first time a successful implementation of such combination on a real robot, without relying on joint torque sensor measurements. Dario Zurlo, Tom Heitmann, Merlin Morlock, Alessandro De Luca 0001 |
ICRA | 3 |