Demo Data from EDBT 2026 / reviewers in the wild / expert
Tjark Harrie Post
dblp:300/4728
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
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 |
Motion planning and robot control · 91% Legged, aerial and field robots · 9% |
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 › manipulator control
aerial manipulator control |
0.3 | 1 | 2017 | Application of substantial and sustained force to vertical surfaces using a quadrotor · ICRA 2017 |
Robotics › Motion planning and robot control › robot control › stabilization control
attitude stabilization |
0.3 | 1 | 2017 | Application of substantial and sustained force to vertical surfaces using a quadrotor · ICRA 2017 |
Robotics › Motion planning and robot control › robot control › contact control › contact task control › robot force control
contact force control |
0.3 | 1 | 2017 | Application of substantial and sustained force to vertical surfaces using a quadrotor · ICRA 2017 |
Robotics › Legged, aerial and field robots › aerial robots
quadrotor |
0.1 | 1 | 2017 | Application of substantial and sustained force to vertical surfaces using a quadrotor · ICRA 2017 |
Methods — techniques the papers use, named apart from their topics
PID control · 0.3LQR-optimized state feedback · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Application of substantial and sustained force to vertical surfaces using a quadrotorabstractIn the field of aerial robotics, one of the key challenges is to enable aerial manipulators to exert substantial forces on the environment. Enabling this will allow the technology to perform meaningful tasks airborne, such as cleaning or grinding surfaces. While in contact and applying a large, continuous force, control of the UAV's attitude is a challenge. In this work, we show that a regular (PID-based) attitude controller is incapable of stabilizing aerial manipulators that apply physical contact forces on the environment that are comparable to the UAV's weight. We present a novel control algorithm that uses an LQR-optimized state feedback on the roll and yaw angle while in contact. Experiments on a UAV of 1.5 kg show that the proposed controller is capable of applying a contact force of over 15 N - equal to the UAV's weight - sustained for several minutes. Han W. Wopereis, Jim Johan Hoekstra, Tjark Harrie Post, Gerrit A. Folkertsma, Stefano Stramigioli, Matteo Fumagalli 0001 |
ICRA | 3 |