Demo Data from SIGIR 2026 / reviewers in the wild / expert
Tim Assman
dblp:135/8698
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
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 · 50% Legged, aerial and field robots · 38% Trustworthy machine learning · 12% |
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 › dynamic stability
balance recovery |
0.2 | 1 | 2013 | Qualitative validation of humanoid robot models through balance recovery side-stepping experiments · ICRA 2013 |
Robotics › Legged, aerial and field robots
humanoid robot |
0.2 | 1 | 2013 | Qualitative validation of humanoid robot models through balance recovery side-stepping experiments · ICRA 2013 |
Machine learning › Trustworthy machine learning
model validation |
0.0 | 1 | 2013 | Qualitative validation of humanoid robot models through balance recovery side-stepping experiments · ICRA 2013 |
Robotics › Motion planning and robot control
robot dynamics |
0.0 | 1 | 2013 | Qualitative validation of humanoid robot models through balance recovery side-stepping experiments · ICRA 2013 |
Methods — techniques the papers use, named apart from their topics
linear inverted pendulum model · 0.23d multi-body model · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Qualitative validation of humanoid robot models through balance recovery side-stepping experimentsabstractDifferent models are used in literature to approximate the complex dynamics of a humanoid robot. Many models use strongly varying model assumptions that neglect the influence of feet, discontinuous ground impact, internal dynamics and coupling between the 3D coronal and sagittal plane dynamics. Often motivation is lacking why a certain model should be chosen or why certain dynamical aspects may or may not be neglected. A simple model like a linear inverted pendulum with low computational cost is frequently used on-line in foot placement algorithms, where model inaccuracy may lead to low control performance. A full 3D multi-body model with higher computational cost is typically used off-line in a simulator, where model inaccuracy may lead to unreliable results. This paper contributes experimental validation of both types of models by comparing them to the real dynamics of the humanoid robot TUlip during balance recovery side-stepping. Hereto, we evaluate the aforementioned most common model assumptions. The validated multi-body model that we implemented in the ROS Gazebo simulator is released on-line. Tim Assman, Pieter van Zutven, Henk Nijmeijer |
ICRA | 1 |