Demo Data from SIGIR 2026 / reviewers in the wild / expert
Maxim Kolesnikov
dblp:26/6170 · also Maxim P. Kolesnikov
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-authorSystems, architecture and hardware · 2 · 2 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.
| Human-computer interaction and pervasive computing
1 paper |
Haptics and multimodal interaction · 44% Human-robot interaction · 44% Immersive interaction · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction › robot learning
sensorimotor learning |
0.1 | 1 | 2009 | PerioSim: Haptic virtual reality simulator for sensorimotor skill acquisition in dentistry · ICRA 2009 |
Haptics and multimodal interaction › haptics
virtual reality haptics |
0.1 | 1 | 2009 | PerioSim: Haptic virtual reality simulator for sensorimotor skill acquisition in dentistry · ICRA 2009 |
Immersive interaction › virtual reality
virtual reality simulation |
0.0 | 1 | 2009 | PerioSim: Haptic virtual reality simulator for sensorimotor skill acquisition in dentistry · ICRA 2009 |
Methods — techniques the papers use, named apart from their topics
trajectory recording · 0.1haptic rendering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | PerioSim: Haptic virtual reality simulator for sensorimotor skill acquisition in dentistryabstractThis paper describes a haptic simulator that has been developed as an aid for the sensorimotor skill acquisition in dentistry. An important feature of the simulator is the ability to generate templates of position and force trajectories for the students to follow. Furthermore, the simulator has a mechanism, haptic playback, to help the students follow and learn these templates. Using this feature, the teacher can perform a procedure in the haptic simulator and record her actions. The trainee is then able to observe the recorded procedure and follow the correct trajectory in the position and force. Several haptic playback techniques are reviewed and the procedure implemented in the simulator is described in detail. We also describe hardware and software components of the simulator and their functionality.We conclude by describing the results of a preliminary classroom evaluation of the simulator. Maxim Kolesnikov, Milos Zefran, Arnold D. Steinberg, Philip G. Bashook |
ICRA | 1 |
| 2007 | Energy-based 6-DOF penetration depth computation for penalty-based haptic rendering algorithmsabstractExisting penalty-based haptic rendering approaches compute penetration depth in strictly translational sense and cannot properly take object rotation into account. We aim to provide a theoretical foundation for computing the penetration depth on the group of rigid-body motions SE(3). We propose a penalty-based six-degrees-of-freedom (6-DOF) haptic rendering algorithm based on determining the closestpoint projection of the inadmissible configuration onto the set of admissible configurations. Energy is used to define the metric on the configuration space. Once the projection is found the 6-DOF wrench can be computed. The configuration space is locally represented with exponential coordinates to make the algorithm more efficient. Numerical examples compare the proposed algorithm with the existing approaches and show its advantages. Maxim Kolesnikov, Milos Zefran |
IROS | 1 |