Demo Data from VLDB 2026 / reviewers in the wild / expert
Victor V. Sazonov
dblp:45/4661
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4Systems, architecture and hardware · 3
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
2 papers |
Autonomous driving · 40% Motion planning and robot control · 30% 3D vision · 30% | |
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Autonomous driving
trajectory prediction |
0.1 | 1 | 2005 | Web-based Teleoperation of the Robot Interacting with Fast Moving Objects · ICRA 2005 |
Human-robot interaction
teleoperation |
0.1 | 1 | 2005 | Web-based Teleoperation of the Robot Interacting with Fast Moving Objects · ICRA 2005 |
Robotics › Motion planning and robot control › motion planning › online motion planning
moving-object interception |
0.0 | 1 | 1998 | Real Time Hand-Eye System: interaction with Moving Objects · ICRA 1998 |
Computer vision › 3D vision › motion estimation
object motion estimation |
0.0 | 1 | 1998 | Real Time Hand-Eye System: interaction with Moving Objects · ICRA 1998 |
Computer vision › 3D vision
stereo vision |
0.0 | 1 | 1998 | Real Time Hand-Eye System: interaction with Moving Objects · ICRA 1998 |
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing |
0.0 | 1 | 1998 | Real Time Hand-Eye System: interaction with Moving Objects · ICRA 1998 |
Methods — techniques the papers use, named apart from their topics
shared autonomy · 0.1motion prediction · 0.1statistical parameter estimation · 0.0dynamical model-based visual processing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Web-based Teleoperation of the Robot Interacting with Fast Moving ObjectsabstractCatching the moving object by a robot manipulator when controlling the robot via the Internet is considered at this paper. The object was the rod on bifilar suspension, performing complicated oscillations. Task statement and capture algorithms are presented. Shared autonomy control was used to implement the capture. Operator forms initial motion of the rod, chooses desired point for capture on the rod and capture instant. Final operation is performed automatically. Operator plans capture strategy using 3D on-line virtual model of the robot and object in its current positions. Capture operation is performed using motion prediction algorithm, based on the object’s motion model. Experimental test-bed, remote control interface are presented. The particulars of the system, the experiments undertaken, current issues, and directions of the future work are discussed. Video film will demonstrate results of the work. Igor R. Belousov, Sviatoslav Chebukov, Victor V. Sazonov |
ICRA | 3 |
| 2004 | Automatic Vision-Based Monitoring of the Spacecraft Docking Approach with the International Space Station
Andrey A. Boguslavsky, Victor V. Sazonov, Sergey M. Sokolov, Alexandr I. Smirnov, Khamzat S. Saigiraev |
ICINCO (2) | 2 |
| 1998 | Real Time Hand-Eye System: interaction with Moving ObjectsabstractThe paper presents the results in controlling the robot manipulator handling the moving object of various types. Two series of experiments were carried out using the rod swinging on the bifilar suspension, and the tennis balls swinging as spherical pendulums. The main part of the experiments with the rod was devoted to finding efficient ways for its fast and reliable capturing. The experiments with the ball were focused on modifying the motion of the ball in such a way for its orbit has the desirable parameters. In particular, the ball was directed to reach the motionless target placed inside the working space, or perform a rendezvous with another ball having an independent free motion. The TV camera supplied the computer with the visual data of the scene. The dynamical models of the motion of the objects were used for statistical processing the visual data and determining the parameters of the motion. These parameters were used for controlling the robot. D. E. Okhotsimsky, Alexander K. Platonov, Igor R. Belousov, Andrey A. Boguslavsky, S. N. Emelianov, Victor V. Sazonov, Sergey M. Sokolov |
ICRA | 6 |
| 1997 | Vision system for automatic capturing a moving object by the robot manipulatorabstractThe paper contents description of the experiments on capturing the moving object by means of a robot manipulator RM-01 (like PUMA 560) with vision system. The object to be grasped is the rod on a bifilar suspension. The upper ends of the fibers are attached to the stable beam which holds a TV camera connected to a computer. Data processing results in the coordinates of the end points of the rod. The algorithm developed gives the possibility to obtain up to 25 pairs of end points per second. The data are subjected to statistical analysis taking into account the dynamic model of the rod motion. The results obtained for the 0.5 s interval allow us to calculate the initial conditions of the rod motion and to predict the motion to several seconds ahead. Analysis of the predicted motion allows us to determine the proper moment of capture, and the position of the manipulator grip at that moment. The capture is implemented in 2-5 s after the start of the process, within 1-2 periods of longitudinal and lateral modes of the rod oscillation. D. E. Okhotsimsky, Alexander K. Platonov, Igor R. Belousov, Andrey A. Boguslavsky, G. K. Borovin, S. N. Yemeljyanov, M. M. Komarov, Victor V. Sazonov, Sergey M. Sokolov |
IROS | 8 |