World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
66
Citations
17993
World Ranking
2321
National Ranking
1158

Rüdiger Dillmann publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Rüdiger Dillmann sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 746 publications — 98th percentile

98% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Rüdiger Dillmann D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Rüdiger Dillmann sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 66 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2012 - IEEE Fellow For contributions to robot programming and human-centerd technologies

Overview

Rüdiger Dillmann is affiliated with the Center for Information Technology in the United States. Their research primarily spans the fields of Engineering and Computer Science, with a focus on various subfields including Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering, Artificial Intelligence, and Mechanical Engineering.

The main topics covered by Dillmann's work include Robot Manipulation and Learning, Robotic Path Planning Algorithms, Modular Robots and Swarm Intelligence, Advanced Memory and Neural Computing, Robotic Locomotion and Control, Robotics and Sensor-Based Localization, and Reinforcement Learning in Robotics.

Some of the recent publications by Dillmann are as follows:

  • Soft-Grasping With an Anthropomorphic Robotic Hand Using Spiking Neurons (2020), published in IEEE Robotics and Automation Letters
  • A spiking network classifies human sEMG signals and triggers finger reflexes on a robotic hand (2020), published in Robotics and Autonomous Systems
  • Benchmarking Highly Parallel Hardware for Spiking Neural Networks in Robotics (2021), published in Frontiers in Neuroscience
  • E-DQN-Based Path Planning Method for Drones in Airsim Simulator under Unknown Environment (2024), published in Biomimetics
  • Distributed Active Learning for Semantic Segmentation on Walking Robots (2021), published in 2021 20th International Conference on Advanced Robotics (ICAR)

Dillmann frequently publishes in venues such as arXiv (Cornell University), 2021 20th International Conference on Advanced Robotics (ICAR), 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), Biomimetics, and IEEE Robotics and Automation Letters.

The scientist has collaborated extensively with coauthors including Arne Roennau, Lea Steffen, Stefan Ulbrich, C. Plasberg, and Stefan Scherzinger.

Dillmann has contributed to book publications with Springer Science+Business Media. Titles include Communications, Signal Processing, and Systems (2022), Sensing Technology (2022), and Recent Advances in Electrical Engineering, Electronics and Energy (2022).

In 2012, Dillmann was recognized as an IEEE Fellow for contributions to robot programming and human-centered technologies.

Best Publications

  • ARMAR-III: An Integrated Humanoid Platform for Sensory-Motor Control

    T. Asfour;K. Regenstein;P. Azad;J. Schroder

  • Teaching and learning of robot tasks via observation of human performance

    Rüdiger Dillmann

  • Design of the TUAT/Karlsruhe humanoid hand

    N. Fukaya;S. Toyama;T. Asfour;R. Dillmann

  • Probabilistic Decision-Making under Uncertainty for Autonomous Driving Using Continuous POMDPs

    Sebastian Brechtel;Tobias Gindele;Rüdiger Dillmann

  • A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments

    Tobias Gindele;Sebastian Brechtel;Rudiger Dillmann

  • The KIT object models database: An object model database for object recognition, localization and manipulation in service robotics

    Alexander Kasper;Zhixing Xue;Rüdiger Dillmann

  • An integrated approach to inverse kinematics and path planning for redundant manipulators

    D. Bertram;J. Kuffner;R. Dillmann;T. Asfour

  • Humanoid motion planning for dual-arm manipulation and re-grasping tasks

    Nikolaus Vahrenkamp;Dmitry Berenson;Tamim Asfour;James Kuffner

  • Imitation Learning of Dual-Arm Manipulation Tasks in Humanoid Robots

    Tamim Asfour;Florian Gyarfas;Pedram Azad;Rudiger Dillmann

  • Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

    Tobias Gindele;Sebastian Brechtel;Rudiger Dillmann

  • Human-like motion of a humanoid robot arm based on a closed-form solution of the inverse kinematics problem

    T. Asfour;R. Dillmann

  • Object-action complexes: Grounded abstractions of sensory-motor processes

    Norbert Krüger;Christopher W. Geib;Justus H. Piater;Ronald P. A. Petrick

  • Incremental Learning of Tasks From User Demonstrations, Past Experiences, and Vocal Comments

    M. Pardowitz;S. Knoop;R. Dillmann;R.D. Zollner

  • Sensor fusion for 3D human body tracking with an articulated 3D body model

    S. Knoop;S. Vacek;R. Dillmann

  • Building elementary robot skills from human demonstration

    M. Kaiser;R. Dillmann

  • RRT∗-Connect: Faster, asymptotically optimal motion planning

    Sebastian Klemm;Jan Oberlander;Andreas Hermann;Arne Roennau

  • Combining Harris interest points and the SIFT descriptor for fast scale-invariant object recognition

    Pedram Azad;Tamim Asfour;Rudiger Dillmann

  • Learning From Humans

    Aude Gemma Billard;Sylvain Calinon;Rüdiger Dillmann

  • Using gesture and speech control for commanding a robot assistant

    O. Rogalla;M. Ehrenmann;R. Zollner;R. Becher

  • Programming by demonstration: dual-arm manipulation tasks for humanoid robots

    R. Zollner;T. Asfour;R. Dillmann

  • Learning Robot Behaviour and Skills Based on Human Demonstration and Advice: The Machine Learning Paradigm

    R. Dillmann;O. Rogalla;M. Ehrenmann;R. Zöliner

Frequent Co-Authors

Tamim Asfour
Tamim Asfour Karlsruhe Institute of Technology
Stefanie Speidel
Stefanie Speidel National Center for Tumor Diseases
Beat P. Müller-Stich
Beat P. Müller-Stich Heidelberg University
Ales Ude
Ales Ude Jožef Stefan Institute
James J. Kuffner
James J. Kuffner Toyota Motor Corporation (United States)
Tim Weyrich
Tim Weyrich University College London
Lena Maier-Hein
Lena Maier-Hein German Cancer Research Center
Gordon Cheng
Gordon Cheng Technical University of Munich
Alexander Verl
Alexander Verl University of Stuttgart
Danica Kragic
Danica Kragic Royal Institute of Technology

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