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Robotic Mechanisms and Dynamics

Robotic Mechanisms and Dynamics is a research topic within Control and Systems Engineering. Science Explorer counts 30k research works in it since 1950. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the kinematic and dynamic analysis, control, optimization, and calibration of robot manipulators, with an emphasis on redundant robots, parallel mechanisms, neural network applications, trajectory planning, workspace analysis, and stiffness optimization.

  • Robot Manipulators
  • Kinematic Analysis
  • Dynamic Modeling
  • Redundant Robots
  • Parallel Mechanisms
  • Neural Networks
  • Trajectory Planning
  • Workspace Analysis
  • Stiffness Optimization
  • Calibration
Research works
30k
fractional, since 1950
In the world top 10%
3k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+13%
the tick is no change
Largest producer
China
54% of the 10 largest, 2022-now

Which countries lead Robotic Mechanisms and Dynamics research?

By volume, China and the United States publish the most (2.1k and 439 works in 2022-now).

By volume, 2022-now

  1. 1 China 2.1k works
  2. 2 United States 439 works
  3. 3 Japan 249 works
  4. 4 India 224 works
  5. 5 Germany 207 works
  6. 6 Italy 177 works
  7. 7 Russia 141 works
  8. 8 France 136 works
  9. 9 United Kingdom 115 works
  10. 10 South Korea 90 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: 54.0%United States: 11.4%Japan: 6.5%India: 5.8%6 others listed: 22.4%54%largest
China2,084 · 54.0%United States439 · 11.4%Japan249 · 6.5%India224 · 5.8%6 others listed866 · 22.4%

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

Which institutions lead Robotic Mechanisms and Dynamics research?

By volume in 2022-now, Harbin Institute of Technology publishes the most Robotic Mechanisms and Dynamics research, followed by Chinese Academy of Sciences and Shanghai Jiao Tong University.

Who are the leading researchers in Robotic Mechanisms and Dynamics?

The most-cited researchers publishing on Robotic Mechanisms and Dynamics include Kalyanmoy Deb and Gábor Marth.

  1. 1 Kalyanmoy Deb United States 171k citations
  2. 2 Gábor Marth United States 167k citations

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

What are the most cited papers in Robotic Mechanisms and Dynamics?

The most cited paper in Robotic Mechanisms and Dynamics is "Real-Time Obstacle Avoidance for Manipulators and Mobile Robots" (Oussama Khatib, 1986), with 7,738 citations. Next come "Probabilistic roadmaps for path planning in high-dimensional configuration spaces" (6,398) and "A Kinematic Notation for Lower-Pair Mechanisms Based on Matrices" (4,551).

Most cited papers
#PaperReleasedCitations
1 Real-Time Obstacle Avoidance for Manipulators and Mobile Robots Oussama Khatib · The International Journal of Robotics Research Mar 1986 7,738
2 Probabilistic roadmaps for path planning in high-dimensional configuration spaces Lydia E. Kavraki, P. Švestka, J.-C. Latombe et al. · IEEE Transactions on Robotics and Automation Open access 1996 6,398
3 A Kinematic Notation for Lower-Pair Mechanisms Based on Matrices Jacques Denavit, Richard S. Hartenberg · Journal of Applied Mechanics Jun 1955 4,551
4 Bettering operation of Robots by learning Suguru Arimoto, Sadao Kawamura, Fumio Miyazaki · Journal of Robotic Systems Jun 1984 3,486
5 A solution for the best rotation to relate two sets of vectors Wolfgang Kabsch · Acta Crystallographica Section A Sep 1976 3,280
All 99 most cited papers, with filters and sorting

Where is Robotic Mechanisms and Dynamics research done?

The largest centres of Robotic Mechanisms and Dynamics research in 2022-now are Beijing (China), Shanghai (China), Nanjing (China) and Harbin (China). Among places with at least 20 works in it, it is an unusually large share of all research in Qinhuangdao, Nantes and Genoa.

Largest cities, 2022-now

  1. 1 BeijingChina 346 works
  2. 2 ShanghaiChina 166 works
  3. 3 NanjingChina 112 works
  4. 4 HarbinChina 108 works
  5. 5 TianjinChina 108 works
  6. 6 WuhanChina 103 works
  7. 7 GuangzhouChina 97 works
  8. 8 HangzhouChina 95 works
  9. 9 TokyoJapan 78 works
  10. 10 Xi'anChina 70 works

Where it is the local speciality

  1. QinhuangdaoCN · 46.6 works22×
  2. NantesFR · 24.4 works8.9×
  3. GenoaIT · 23.0 works8.0×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Robotic Mechanisms and Dynamics than the world average.

See Robotic Mechanisms and Dynamics on the map

Where is the best place to study Robotic Mechanisms and Dynamics?

Among universities, judged by research, Harbin Institute of Technology, Tsinghua University and Shanghai Jiao Tong University 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 23.2%fractional works in this field (log) →share of work in the world top 10% →Huazhong University …Tsinghua UniversityHarbin Institute of …Shanghai Jiao Tong U…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Harbin Institute of TechnologyChina 65.818.9%12.7×93 +30.3%
2Tsinghua UniversityChina 63.019.0%5.8×60 +38.0%
3Shanghai Jiao Tong UniversityChina 60.718.5%4.9×63 +60.7%
4Huazhong University of Science and TechnologyChina 60.524.1%5.3×43 +64.9%
5Lanzhou UniversityChina 60.541.2%3.3×10 +91.1%
6Hong Kong Polytechnic UniversityChina 58.327.8%3.5×14 +20.1%
7Chinese University of Hong KongChina 58.129.8%4.7×16 +100.4%
8Sun Yat-sen UniversityChina 53.521.2%2.8×26 +43.5%
9Nanjing University of Aeronautics and AstronauticsChina 51.511.0%9.6×38 +75.1%
10Tianjin UniversityChina 51.520.5%6.2×34 -4.2%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Robotic Mechanisms and Dynamics, country by country

Is Robotic Mechanisms and Dynamics research growing?

Output in 2022-2025 was 13% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Robotic Mechanisms and Dynamics.

still counting19801990200020102020
grewheldshrank

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

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Robotic Mechanisms and Dynamics as a percentage of every work published that year, 0.024% in 2024.

still counting0.050%0.10%Robotic Mechanisms and Dynamics0.024% in 202519801990200020102020

Fractional works of Robotic Mechanisms and Dynamics over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Robotic Mechanisms and Dynamics9.9% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

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.

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