Peter Pástor

7.6k citations
30 papers · 4.3k indexed · 4 hit papers · h-index 23

Peter Pástor

30 papers receiving 4.2k citations

Hit Papers

How to train your robot ...32320092026201420202505007501000

Peers

Peter Pástor
Comparison fields: 5 of 103
  • Control and Systems Engineering 3.1k
  • Computer Vision and Pattern Recognition 1.3k
  • Artificial Intelligence 1.3k
  • Biomedical Engineering 1.8k
  • Human-Computer Interaction 158
Replace Aleš Ude with:
Aleš Ude Slovenia
Jun Nakanishi Japan
Oliver Brock Germany
Keigo Watanabe Japan
Dmitry Berenson United States
Sylvain Calinon Switzerland
Sachin Chitta United States
Kei Okada Japan
Jens Kober Netherlands
Russ Tedrake United States
Peter Pástor relative to Aleš Ude Slovenia Aleš Ude's profile →
Citations per field
00.5×1.5×
Aleš Ude · 1×
Citations per year

Countries citing papers authored by Peter Pástor

Since Specialization
Citations

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

Fields of papers citing papers by Peter Pástor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Peter Pástor, 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 Peter Pástor Line = papers co-authored together Peter Pástor links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201910
2
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
201871
3
End-to-End Learning of Semantic Grasping
201713
4 201479
5
Experiments with a hierarchical inverse dynamics controller on a torque-controlled humanoid
20138
6 201321
7 201341
8 201371
9 201382
10 201348
11 201277
12
Learning force control policies for compliant robotic manipulation
201210
13 201265
14 2011103
15 2011144
16 201127
17
Learning and generalization of motor skills by learning from demonstrationbreakdown →
2009466
18 200923
19 2009123
20 2009206

About Peter Pástor

Peter Pástor is a scholar working on Control and Systems Engineering, Biomedical Engineering, Artificial Intelligence, Orthopedics and Sports Medicine and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 4.3k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (23 papers), Reinforcement Learning in Robotics (10 papers), Robotic Locomotion and Control (9 papers), Prosthetics and Rehabilitation Robotics (6 papers), Muscle activation and electromyography studies (6 papers), Robotic Mechanisms and Dynamics (5 papers), Motor Control and Adaptation (3 papers) and Soft Robotics and Applications (3 papers). The work is most often cited by research in Control and Systems Engineering (3.1k citations), Computer Vision and Pattern Recognition (1.3k citations), Artificial Intelligence (1.3k citations), Biomedical Engineering (1.8k citations) and Human-Computer Interaction (158 citations). Peter Pástor has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Mrinal Kalakrishnan, Stefan Schaal, Stefan Schaal, H. Hoffmann, Auke Jan Ijspeert, Jun Nakanishi, Ludovic Righetti, Evangelos A. Theodorou, Sachin Chitta and Tamim Asfour. Their work appears in journals such as The International Journal of Robotics Research, Autonomous Robots, Neural Computation, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems and arXiv (Cornell University).

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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