Jae-Bok Song

2.6k total citations
166 papers, 1.8k citations indexed

About

Jae-Bok Song is a scholar working on Control and Systems Engineering, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jae-Bok Song has authored 166 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Control and Systems Engineering, 66 papers in Biomedical Engineering and 63 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jae-Bok Song's work include Robot Manipulation and Learning (65 papers), Robotics and Sensor-Based Localization (49 papers) and Robotic Path Planning Algorithms (40 papers). Jae-Bok Song is often cited by papers focused on Robot Manipulation and Learning (65 papers), Robotics and Sensor-Based Localization (49 papers) and Robotic Path Planning Algorithms (40 papers). Jae-Bok Song collaborates with scholars based in South Korea, United States and Japan. Jae-Bok Song's 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 and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Access and IEEE Transactions on Industry Applications.

In The Last Decade

Jae-Bok Song

138 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jae-Bok Song South Korea 24 1.0k 862 452 449 323 166 1.8k
Jae‐Bok Song South Korea 23 865 0.9× 529 0.6× 459 1.0× 475 1.1× 403 1.2× 119 1.6k
Tsutomu Hasegawa Japan 20 713 0.7× 507 0.6× 275 0.6× 641 1.4× 382 1.2× 195 1.5k
Torsten Kröger Germany 19 1.3k 1.2× 528 0.6× 395 0.9× 575 1.3× 228 0.7× 63 1.7k
Wyatt S. Newman United States 25 957 0.9× 606 0.7× 515 1.1× 332 0.7× 189 0.6× 106 1.7k
Weiwei Wan Japan 24 1.1k 1.1× 558 0.6× 354 0.8× 596 1.3× 255 0.8× 173 1.7k
Nikos Aspragathos Greece 27 1.3k 1.3× 694 0.8× 780 1.7× 497 1.1× 148 0.5× 136 2.7k
Akio Namiki Japan 25 1.3k 1.3× 1.2k 1.4× 439 1.0× 589 1.3× 312 1.0× 136 2.3k
Dongming Gan United Arab Emirates 27 1.3k 1.3× 1.0k 1.2× 478 1.1× 172 0.4× 193 0.6× 105 1.9k
Shahram Payandeh Canada 22 675 0.7× 778 0.9× 589 1.3× 565 1.3× 134 0.4× 205 1.9k
Arne Roennau Germany 19 499 0.5× 403 0.5× 298 0.7× 451 1.0× 320 1.0× 115 1.3k

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 of co-authors of Jae-Bok Song

This figure shows the co-authorship network connecting the top 25 collaborators of Jae-Bok Song. A scholar is included among the top collaborators of Jae-Bok Song based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jae-Bok Song. Jae-Bok Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Song, Jae-Bok, et al.. (2025). Adaptive three-finger grippers using a single actuator. Journal of Mechanical Science and Technology. 39(3). 1435–1442.
2.
Song, Jae-Bok, et al.. (2024). Similar assembly state discriminator for reinforcement learning-based robotic connector assembly. Robotics and Computer-Integrated Manufacturing. 91. 102842–102842.
3.
Song, Jae-Bok, et al.. (2024). A Gripper Capable of Screw Fastening and Gripping With a Single Driving Source. International Journal of Control Automation and Systems. 22(9). 2882–2890.
4.
Kim, Hyeonseong, Jae-Bok Song, & Kibok Lee. (2024). I-F Startup with Reactive Power-based MRAS for Model Predictive Current Controlled SPMSM Drive. 6065–6069. 1 indexed citations
5.
Song, Jae-Bok, et al.. (2023). Assembly of low-stiffness parts through admittance control with adaptive stiffness. Robotics and Computer-Integrated Manufacturing. 86. 102678–102678. 11 indexed citations
6.
Ahn, Kuk-Hyun, et al.. (2023). Robotic assembly strategy via reinforcement learning based on force and visual information. Robotics and Autonomous Systems. 164. 104399–104399. 20 indexed citations
7.
Kang, Minsu, et al.. (2022). Leg Structure based on Counterbalance Mechanism for Environmental Adaptive Robot. Journal of the Korean Society of Manufacturing Process Engineers. 21(8). 9–18. 1 indexed citations
8.
Song, Jae-Bok, et al.. (2018). Data-based Assembly Failure State Estimation of mobile IT parts using a 6 DOF manipulator. International Conference on Control, Automation and Systems. 1703–1707. 1 indexed citations
9.
Ahn, Kuk-Hyun, et al.. (2016). Torque control based sensorless hand guiding for direct robot teaching. 745–750. 32 indexed citations
10.
Kim, Mincheol, et al.. (2015). Sensorless collision detection for safe human-robot collaboration. 2392–2397. 48 indexed citations
11.
12.
Kim, Byeong-Sang, et al.. (2012). A strategy for connector assembly using impedance control for industrial robots. International Conference on Control, Automation and Systems. 1433–1435. 3 indexed citations
13.
Kim, Chul Sung, Chang‐Woo Park, Bong-Seok Kim, Jae-Bok Song, & Jung-Hoon Hwang. (2012). Design of robotic surgical instrument for minimally invasive surgical robot system. International Conference on Control, Automation and Systems. 1720–1723. 1 indexed citations
14.
Park, Jung-Jun & Jae-Bok Song. (2009). Collision analysis and evaluation of collision safety for service robots working in human environments. 1–6. 17 indexed citations
15.
Kim, Byeong-Sang, Jung-Jun Park, Jae-Bok Song, & Hong‐Seok Kim. (2006). Double Actuator Unit based on the Planetary Gear Train Capable of Position/Force Control. The Journal of Korea Robotics Society. 1(1). 81–88. 1 indexed citations
16.
Kim, Bong-Seok, et al.. (2005). Development of a Joint Torque Sensor Fully Integrated with an Actuator. 제어로봇시스템학회 국제학술대회 논문집. 1679–1683. 7 indexed citations
17.
Song, Jae-Bok, et al.. (2005). Reduction in Sample Size Using Topological Information for Monte Carlo Localization. 제어로봇시스템학회 국제학술대회 논문집. 901–905. 1 indexed citations
18.
Song, Jae-Bok, et al.. (2003). Thinning Based Global Topological Map Building with Application to Localization. 822–827. 1 indexed citations
19.
Song, Jae-Bok, et al.. (2003). Installation Error Calibration by Using Levenberg-Marquardt Method on a Cubic Parallel Manipulator. Journal of the Korean Society for Precision Engineering. 20(2). 177. 2 indexed citations
20.
Lee, Jong‐Won, et al.. (2000). Regrasp Planner Using Look-up Table. Transactions of the Korean Society of Mechanical Engineers A. 24(4). 848–857. 1 indexed citations

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026