Jae-Bok Song

2.6k citations
166 papers · 1.8k indexed · h-index 24

Jae-Bok Song

138 papers receiving 1.8k citations

Peers

Jae-Bok Song
Comparison fields: 5 of 95
  • Control and Systems Engineering 1.0k
  • Computer Vision and Pattern Recognition 449
  • Biomedical Engineering 862
  • Industrial and Manufacturing Engineering 166
  • Human-Computer Interaction 75
Replace Weiwei Wan with:
Weiwei Wan Japan
Fabrizio Flacco Italy
Torsten Kröger Germany
Jae‐Bok Song South Korea
Wyatt S. Newman United States
Arne Roennau Germany
David Navarro-Alarcón Hong Kong
Tsutomu Hasegawa Japan
Jaeheung Park South Korea
Ruediger Dillmann Germany
Jae-Bok Song relative to Weiwei Wan Japan Weiwei Wan's profile →
Citations per field
00.5×1.5×2.4×
Weiwei Wan · 1×
Citations per year

Countries citing papers authored by Jae-Bok Song

Since Specialization
Citations

This map shows the geographic impact of Jae-Bok Song's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jae-Bok Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jae-Bok Song more than expected).

Fields of papers citing papers by Jae-Bok Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae-Bok Song. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jae-Bok Song. The network helps show where Jae-Bok Song may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jae-Bok Song, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jae-Bok Song Line = papers co-authored together Jae-Bok Song links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20240
3 20240
4 20241
5 202311
6 202320
7 20221
8
Data-based Assembly Failure State Estimation of mobile IT parts using a 6 DOF manipulator
20181
9 201632
10 201548
11 20155
12
A strategy for connector assembly using impedance control for industrial robots
20123
13
Design of robotic surgical instrument for minimally invasive surgical robot system
20121
14
Collision analysis and evaluation of collision safety for service robots working in human environments
200917
15
Double Actuator Unit based on the Planetary Gear Train Capable of Position/Force Control
20061
16
Development of a Joint Torque Sensor Fully Integrated with an Actuator
20057
17
Reduction in Sample Size Using Topological Information for Monte Carlo Localization
20051
18
Thinning Based Global Topological Map Building with Application to Localization
20031
19
Installation Error Calibration by Using Levenberg-Marquardt Method on a Cubic Parallel Manipulator
20032
20 20001

About Jae-Bok Song

Jae-Bok Song is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 166 papers that have together received 1.8k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (65 papers), Robotics and Sensor-Based Localization (49 papers), Robotic Path Planning Algorithms (40 papers), Robotic Mechanisms and Dynamics (28 papers), Prosthetics and Rehabilitation Robotics (27 papers), Soft Robotics and Applications (27 papers), Teleoperation and Haptic Systems (21 papers) and Robotic Locomotion and Control (21 papers). The work is most often cited by research in Control and Systems Engineering (1.0k citations), Computer Vision and Pattern Recognition (449 citations) and Biomedical Engineering (862 citations). Jae-Bok Song has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Byeong-Sang Kim, Hwi-Su Kim, Jung-Jun Park, Soo‐Yong Lee, Munsang Kim, Jung-Jun Park, Mincheol Kim, Kuk-Hyun Ahn, Yong‐Ju Lee and Hong‐Seok Kim.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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