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Robot Manipulation and Learning

Robot Manipulation and Learning is a research topic within Control and Systems Engineering. Science Explorer counts 33k research works in it since 1956. 20.7% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on robotic grasping, learning from demonstration, deep learning for object pose estimation, human-robot collaboration, and sensor-based robot systems. It explores topics such as dynamical movement primitives, impedance control, and safe interaction between humans and robots.

  • Robot Learning
  • Grasping
  • Deep Learning
  • Human-Robot Collaboration
  • Object Pose Estimation
  • Dynamical Movement Primitives
  • Impedance Control
  • 3D Object Recognition
  • Sensor-Based Robot Systems
  • Safe Human-Robot Interaction
Research works
33k
fractional, since 1956
In the world top 10%
6.8k
per year above
Top-10% rate
20.7%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+42%
the tick is no change

Which countries lead Robot Manipulation and Learning research?

By volume, China and the United States publish the most (2.5k and 1k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 2.5k works
  2. 2 United States 1k works
  3. 3 Japan 634 works
  4. 4 Germany 479 works
  5. 5 Italy 337 works
  6. 6 United Kingdom 330 works
  7. 7 India 282 works
  8. 8 South Korea 240 works
  9. 9 France 168 works
  10. 10 Canada 151 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: 40.3%United States: 17.1%Japan: 10.3%Germany: 7.8%6 others listed: 24.5%40%largest
China2,475 · 40.3%United States1,050 · 17.1%Japan634 · 10.3%Germany479 · 7.8%6 others listed1,507 · 24.5%

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

Which institutions lead Robot Manipulation and Learning research?

By volume in 2022–2025, Harbin Institute of Technology publishes the most Robot Manipulation and Learning research, followed by Shanghai Jiao Tong University and Tsinghua University.

Who are the leading researchers in Robot Manipulation and Learning?

The most-cited researchers publishing on Robot Manipulation and Learning include Li Fei-Fei, Jitendra Malik and Wolfram Burgard.

  1. 1 Li Fei-Fei United States 17k citations
  2. 2 Jitendra Malik United States 12k citations
  3. 3 Wolfram Burgard Germany 6.3k citations

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

Where is Robot Manipulation and Learning research done?

The largest centres of Robot Manipulation and Learning research in 2022–2025 are Beijing (China), Shanghai (China), Tokyo (Japan) and Harbin (China). Among places with at least 20 works in it, it is an unusually large share of all research in Genoa.

Largest cities, 2022–2025

  1. 1 Beijing China 510 works
  2. 2 Shanghai China 242 works
  3. 3 Tokyo Japan 237 works
  4. 4 Harbin China 129 works
  5. 5 Nanjing China 125 works
  6. 6 Hangzhou China 125 works
  7. 7 Wuhan China 122 works
  8. 8 Guangzhou China 120 works
  9. 9 Shenzhen China 109 works
  10. 10 Seoul South Korea 105 works

Where it is the local speciality

  1. GenoaIT · 58.1 works13×
← less than its size predictsmore →

Location quotient: how much more of its research is in Robot Manipulation and Learning than the world average.

See Robot Manipulation and Learning on the map

Where is the best place to study Robot Manipulation and Learning?

Among universities, judged by research, Hong Kong Polytechnic University, Carnegie Mellon University and Technical University of Munich 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 29.66%fractional works in this node (log) →share in the world top 10% →Hong Kong Polytechnic University: 22, 42.7%Carnegie Mellon University: 52, 27.5%Technical University of Munich: 65, 22.8%University of Patras: 15, 39.9%Singapore University of Technology and Design: 11, 16.1%University of California, Berkeley: 24, 41.5%Tsinghua University: 78, 25.9%Massachusetts Institute of Technology: 31, 34.2%Harbin Institute of Technology: 103, 14.1%KTH Royal Institute of Technology: 22, 31.9%Hong Kong Polytechni…University of PatrasCarnegie Mellon Univ…Technical University…
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 Hong Kong Polytechnic UniversityHong Kong 67.542.7%3.4×22 +205.8%
2 Carnegie Mellon UniversityUnited States 65.427.5%16.9×52 +20.3%
3 Technical University of MunichGermany 65.022.8%10.8×65 +7.0%
4 University of PatrasGreece 64.539.9%8.2×15 +112.3%
5 Singapore University of Technology and DesignSingapore 62.116.1%16.2×11 +359.5%
6 University of California, BerkeleyUnited States 62.041.5%3.8×24 +298.9%
7 Tsinghua UniversityChina 61.925.9%5.2×78 +163.5%
8 Massachusetts Institute of TechnologyUnited States 60.934.2%6.7×31 +70.4%
9 Harbin Institute of TechnologyChina 58.814.1%8.2×103 +76.7%
10 KTH Royal Institute of TechnologySweden 58.131.9%7.9×22 -2.6%

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 Robot Manipulation and Learning research growing?

Output in 2018–2022 was 42% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Robot Manipulation and Learning.

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.