2026 Rüdiger Dillmann: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	66	2321	2251	1157	1116	746	17993

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

515
Citations
Teaching and learning of robot tasks via observation of human performance

Rüdiger Dillmann

417
Citations
Design of the TUAT/Karlsruhe humanoid hand

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

343
Citations
Probabilistic Decision-Making under Uncertainty for Autonomous Driving Using Continuous POMDPs

Sebastian Brechtel;Tobias Gindele;Rüdiger Dillmann

327
Citations
A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments

Tobias Gindele;Sebastian Brechtel;Rudiger Dillmann

264
Citations
The KIT object models database: An object model database for object recognition, localization and manipulation in service robotics

Alexander Kasper;Zhixing Xue;Rüdiger Dillmann

259
Citations
An integrated approach to inverse kinematics and path planning for redundant manipulators

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

242
Citations
Humanoid motion planning for dual-arm manipulation and re-grasping tasks

Nikolaus Vahrenkamp;Dmitry Berenson;Tamim Asfour;James Kuffner

226
Citations
Imitation Learning of Dual-Arm Manipulation Tasks in Humanoid Robots

Tamim Asfour;Florian Gyarfas;Pedram Azad;Rudiger Dillmann

225
Citations
Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

Tobias Gindele;Sebastian Brechtel;Rudiger Dillmann

225
Citations
Human-like motion of a humanoid robot arm based on a closed-form solution of the inverse kinematics problem

T. Asfour;R. Dillmann

223
Citations
Object-action complexes: Grounded abstractions of sensory-motor processes

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

211
Citations
Incremental Learning of Tasks From User Demonstrations, Past Experiences, and Vocal Comments

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

211
Citations
Sensor fusion for 3D human body tracking with an articulated 3D body model

S. Knoop;S. Vacek;R. Dillmann

210
Citations
Building elementary robot skills from human demonstration

M. Kaiser;R. Dillmann

201
Citations
RRT∗-Connect: Faster, asymptotically optimal motion planning

Sebastian Klemm;Jan Oberlander;Andreas Hermann;Arne Roennau

194
Citations
Combining Harris interest points and the SIFT descriptor for fast scale-invariant object recognition

Pedram Azad;Tamim Asfour;Rudiger Dillmann

188
Citations
Learning From Humans

Aude Gemma Billard;Sylvain Calinon;Rüdiger Dillmann

186
Citations
Using gesture and speech control for commanding a robot assistant

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

169
Citations
Programming by demonstration: dual-arm manipulation tasks for humanoid robots

R. Zollner;T. Asfour;R. Dillmann

168
Citations
Learning Robot Behaviour and Skills Based on Human Demonstration and Advice: The Machine Learning Paradigm

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

166
Citations

Frequent Co-Authors

Tamim Asfour Karlsruhe Institute of Technology

Stefanie Speidel National Center for Tumor Diseases

Ales Ude Jožef Stefan Institute

James J. Kuffner Toyota Motor Corporation (United States)

Tim Weyrich University College London

Gordon Cheng Technical University of Munich

Lena Maier-Hein German Cancer Research Center

Nancy S. Pollard Carnegie Mellon University

Alexander Verl University of Stuttgart

Danica Kragic Royal Institute of Technology

External Links

Google Scholar page

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