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Alexander K. Platonov

dblp:144/8587 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 1998
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3Systems, architecture and hardware · 2Graphics, computer vision, multimedia, augmented reality and games · 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
2 papers
Motion planning and robot control · 49% 3D vision · 48% Legged, aerial and field robots · 2%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › motion planning › online motion planning
moving-object interception
0.011998
Real Time Hand-Eye System: interaction with Moving Objects · ICRA 1998
Computer vision › 3D vision › motion estimation
object motion estimation
0.011998
Real Time Hand-Eye System: interaction with Moving Objects · ICRA 1998
Computer vision › 3D vision
stereo vision
0.011998
Real Time Hand-Eye System: interaction with Moving Objects · ICRA 1998
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing
0.011998
Real Time Hand-Eye System: interaction with Moving Objects · ICRA 1998
Robotics › Legged, aerial and field robots › legged robots
legged robot locomotion
0.011973
Control Algorithm of the Walker Climbing Over Obstacles · IJCAI 1973
Robotics › Legged, aerial and field robots › rough terrain locomotion
obstacle climbing
0.011973
Control Algorithm of the Walker Climbing Over Obstacles · IJCAI 1973
Robotics › Motion planning and robot control
robot control
0.011973
Control Algorithm of the Walker Climbing Over Obstacles · IJCAI 1973
Robotics › Legged, aerial and field robots
walking control
0.011973
Control Algorithm of the Walker Climbing Over Obstacles · IJCAI 1973

Methods — techniques the papers use, named apart from their topics

statistical parameter estimation · 0.0dynamical model-based visual processing · 0.0
YearPublicationVenuePosition
1998 Real Time Hand-Eye System: interaction with Moving Objects
abstract
The 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
ICRA2
1997 Vision system for automatic capturing a moving object by the robot manipulator
abstract
The 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
IROS2
1973 Control Algorithm of the Walker Climbing Over Obstacles
D. E. Okhotsimsky, Alexander K. Platonov
IJCAI2