What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Computer vision
His primary scientific interests are in Control theory, Simulation, Robot, Mobile robot and Actuator.
His work carried out in the field of Control theory brings together such families of science as Stiffness and Motion control.
His Simulation study combines topics in areas such as Passivity, Robot kinematics, Robotic arm and Service robot.
His study looks at the relationship between Robot and fields such as Computer vision, as well as how they intersect with chemical problems.
The concepts of his Mobile robot study are interwoven with issues in Optical flow, Feature extraction and Motion planning.
His work in Actuator addresses subjects such as Torque, which are connected to disciplines such as Joint stiffness and Observer.
His most cited work include:
- Control logic for an electric power steering system using assist motor (187 citations)
- Position control of a Stewart platform using inverse dynamics control with approximate dynamics (134 citations)
- Hybrid dual actuator unit: A design of a variable stiffness actuator based on an adjustable moment arm mechanism (86 citations)
What are the main themes of his work throughout his whole career to date?
Jae-Bok Song focuses on Robot, Artificial intelligence, Computer vision, Control theory and Mobile robot.
His Robot research is multidisciplinary, relying on both Simulation and Robotic arm.
As a part of the same scientific study, Jae-Bok Song usually deals with the Simulation, concentrating on Mobile manipulator and frequently concerns with Teleoperation.
His Computer vision research includes themes of Simultaneous localization and mapping, Odometry and Extended Kalman filter.
His Control theory research includes elements of Control engineering and Stiffness.
His Mobile robot study incorporates themes from Motion planning and Motion control.
He most often published in these fields:
- Robot (42.62%)
- Artificial intelligence (40.71%)
- Computer vision (33.61%)
What were the highlights of his more recent work (between 2016-2021)?
- Robot (42.62%)
- Artificial intelligence (40.71%)
- Computer vision (33.61%)
In recent papers he was focusing on the following fields of study:
Jae-Bok Song mostly deals with Robot, Artificial intelligence, Computer vision, Control theory and Robotic arm.
His Robot study combines topics from a wide range of disciplines, such as Simulation, Torque, Trajectory and Coil spring.
His work on Torque sensor as part of general Torque study is frequently linked to Collision detection, bridging the gap between disciplines.
His work in Artificial intelligence covers topics such as Pattern recognition which are related to areas like Feature, Image and Frequency domain.
His Computer vision research is multidisciplinary, incorporating elements of Mobile robot navigation, Cluster analysis and Mobile robot.
Jae-Bok Song has researched Control theory in several fields, including Exoskeleton, Mechanism and Payload.
Between 2016 and 2021, his most popular works were:
- Assembly process monitoring algorithm using force data and deformation data (16 citations)
- An Overview on Principles for Energy Efficient Robot Locomotion. (14 citations)
- Data augmentation using synthesized images for object detection (8 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Computer vision
His scientific interests lie mostly in Robot, Artificial intelligence, Robotic arm, Computer vision and Torque sensor.
His Robot research integrates issues from Control engineering, Algorithm, Simulation and Trajectory.
Jae-Bok Song combines subjects such as Dynamic simulation and Control theory with his study of Robotic arm.
Jae-Bok Song studies Harmonic drive, a branch of Control theory.
His Computer vision research is multidisciplinary, incorporating perspectives in Mobile robot navigation, Robot calibration, Robotics, Service robot and Mobile robot.
His research integrates issues of Representation and Sonar in his study of Mobile robot.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
