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Control and Dynamics of Mobile Robots

Control and Dynamics of Mobile Robots is a research topic within Control and Systems Engineering. Science Explorer counts 22k research works in it since 1950. 17.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the control and navigation of nonholonomic mobile robots, addressing challenges such as adaptive control, trajectory tracking, nonholonomic constraints, feedback control, dynamic modeling, path planning, sliding mode control, omnidirectional robots, robust stabilization, and the use of neural networks for control.

  • Adaptive Control
  • Trajectory Tracking
  • Nonholonomic Constraints
  • Feedback Control
  • Dynamic Modeling
  • Path Planning
  • Sliding Mode Control
  • Omnidirectional Robots
  • Robust Stabilization
  • Neural Networks
Research works
22k
fractional, since 1950
In the world top 10%
3.7k
per year above
Top-10% rate
17.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+17%
the tick is no change

Which countries lead Control and Dynamics of Mobile Robots research?

By volume, China and the United States publish the most (1.9k and 255 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.9k works
  2. 2 United States 255 works
  3. 3 India 240 works
  4. 4 Japan 200 works
  5. 5 Russia 154 works
  6. 6 South Korea 103 works
  7. 7 Mexico 86 works
  8. 8 Vietnam 83 works
  9. 9 Iran 73 works
  10. 10 Italy 71 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 60.0%United States: 8.1%India: 7.6%Japan: 6.3%6 others listed: 18.0%60%largest
China1,898 · 60.0%United States255 · 8.1%India240 · 7.6%Japan200 · 6.3%6 others listed569 · 18.0%

Shares of the rows listed above, not of the whole node.

Which institutions lead Control and Dynamics of Mobile Robots research?

By volume in 2022–2025, Beijing Institute of Technology publishes the most Control and Dynamics of Mobile Robots research, followed by Harbin Institute of Technology and Beihang University.

Who are the leading researchers in Control and Dynamics of Mobile Robots?

The most-cited researchers publishing on Control and Dynamics of Mobile Robots include Wolfram Burgard, Frank L. Lewis and C. L. Philip Chen.

  1. 1 Wolfram Burgard Germany 6.3k citations
  2. 2 Frank L. Lewis United States 3.8k citations
  3. 3 C. L. Philip Chen Macau 3.6k citations
  4. 4 Roland Siegwart Switzerland 3.3k citations
  5. 5 Lihua Xie Singapore 3.2k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Control and Dynamics of Mobile Robots research done?

The largest centres of Control and Dynamics of Mobile Robots research in 2022–2025 are Beijing (China), Nanjing (China), Shanghai (China) and Harbin (China). Among places with at least 20 works in it, it is an unusually large share of all research in Harbin and Hanoi.

Largest cities, 2022–2025

  1. 1 Beijing China 310 works
  2. 2 Nanjing China 126 works
  3. 3 Shanghai China 118 works
  4. 4 Harbin China 106 works
  5. 5 Xi'an China 97 works
  6. 6 Wuhan China 80 works
  7. 7 Moscow Russia 71 works
  8. 8 Tokyo Japan 68 works
  9. 9 Tianjin China 67 works
  10. 10 Hangzhou China 62 works

Where it is the local speciality

  1. HarbinCN · 105.7 works6.3×
  2. HanoiVN · 40.1 works5.9×
← less than its size predictsmore →

Location quotient: how much more of its research is in Control and Dynamics of Mobile Robots than the world average.

See Control and Dynamics of Mobile Robots on the map

Where is the best place to study Control and Dynamics of Mobile Robots?

Among universities, judged by research, Dalian Maritime University, Northwestern Polytechnical University and Harbin Institute of Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 25.23%fractional works in this node (log) →share in the world top 10% →Dalian Maritime University: 27, 26.3%Northwestern Polytechnical University: 42, 27.3%Harbin Institute of Technology: 61, 22.8%Beijing Institute of Technology: 63, 13.9%Beihang University: 49, 16.4%Harbin Engineering University: 29, 25.6%Jiangsu University: 18, 43.5%Nanjing University of Aeronautics and Astronautics: 41, 16.1%Shanghai Maritime University: 9, 26.8%Liaoning University of Technology: 12, 33.6%Northwestern Polytec…Dalian Maritime Univ…Harbin Institute of …Beijing Institute of…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Dalian Maritime UniversityChina 71.126.3%17.9×27 +370.0%
2 Northwestern Polytechnical UniversityChina 66.627.3%8.8×42 +88.5%
3 Harbin Institute of TechnologyChina 62.022.8%9.0×61 +4.6%
4 Beijing Institute of TechnologyChina 60.413.9%12.8×63 +29.5%
5 Beihang UniversityChina 59.516.4%10.7×49 +26.8%
6 Harbin Engineering UniversityChina 58.725.6%13.3×29 +3.6%
7 Jiangsu UniversityChina 58.343.5%5.9×18 +26.6%
8 Nanjing University of Aeronautics and AstronauticsChina 57.316.1%11.0×41 +27.0%
9 Shanghai Maritime UniversityChina 55.426.8%8.5×9 +180.0%
10 Liaoning University of TechnologyChina 54.833.6%39.9×12 +6.6%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Control and Dynamics of Mobile Robots research growing?

Output in 2018–2022 was 17% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Control and Dynamics of Mobile Robots.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.