Peng Song

771 citations
18 papers · 482 indexed · h-index 12

Peng Song

18 papers receiving 458 citations

Peers

Peng Song
Comparison fields: 5 of 65
  • Control and Systems Engineering 333
  • Computational Theory and Mathematics 67
  • Biomedical Engineering 167
  • Mechanical Engineering 126
  • Automotive Engineering 39
Replace Yoshikazu Hayakawa with:
Yoshikazu Hayakawa Japan
Siddharth P. Nagarkatti United States
Ph. Müllhaupt Switzerland
A. Hernández Spain
J. Jim Zhu United States
Hubert Gattringer Austria
Mehdi Keshmiri Iran
A.M. Formal'skii Russia
Frank Génot France
Ammar Al-Jodah Australia
Peng Song relative to Yoshikazu Hayakawa Japan Yoshikazu Hayakawa's profile →
Citations per field
00.5×3.7×
Yoshikazu Hayakawa · 1×
Citations per year

Countries citing papers authored by Peng Song

Since Specialization
Citations

This map shows the geographic impact of Peng 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 Peng Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peng Song more than expected).

Fields of papers citing papers by Peng Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peng 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 Peng Song. The network helps show where Peng Song may publish in the future.

Co-authorship network

The 22 scholars most cited alongside Peng 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 Peng Song Line = papers co-authored together Peng Song links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 20227
2 202128
3 201922
4 2019107
5 201727
6 20104
7 20063
8 200522
9 20054
10 200459
11 200417
12 200312
13 200219
14 200224
15
Modeling, analysis and simulation of multibody systems with contact and friction
200211
16
A Framework for Scalable Cooperative Navigation of Autonomous Vehicles
20012
17 2000104
18 199910

About Peng Song

Peng Song is a scholar working on Control and Systems Engineering, Computational Theory and Mathematics, Automotive Engineering, Mechanics of Materials and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 482 indexed citations. Recurring topics across this work include Dynamics and Control of Mechanical Systems (7 papers), Robot Manipulation and Learning (7 papers), Robotic Mechanisms and Dynamics (5 papers), Contact Mechanics and Variational Inequalities (3 papers), Soft Robotics and Applications (3 papers), Robotic Path Planning Algorithms (3 papers), Mechanical stress and fatigue analysis (2 papers) and Prosthetics and Rehabilitation Robotics (2 papers). The work is most often cited by research in Control and Systems Engineering (333 citations), Computational Theory and Mathematics (67 citations), Biomedical Engineering (167 citations), Mechanical Engineering (126 citations) and Automotive Engineering (39 citations). Peng Song has collaborated with scholars based in United States, China and Denmark. Frequent co-authors include Xuping Zhang, Yueqing Yu, V. Kumar, Jong‐Shi Pang, Pierre E. Dupont, Vijay Kumar, Vijay Kumar, M. Yashima, Bowen Cai and Xiao Huang. Their work appears in journals such as Remote Sensing, Robotica, SIAM Journal on Numerical Analysis, Journal of Applied Mechanics and IEEE Robotics and Automation Letters.

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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