H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology H-index 30 Citations 3,964 198 World Ranking 7038 National Ranking 256

Research.com Recognitions

Awards & Achievements

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

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary scientific interests are in Artificial intelligence, Robot, Humanoid robot, Computer vision and Human–computer interaction. His work focuses on many connections between Artificial intelligence and other disciplines, such as Machine learning, that overlap with his field of interest in Pattern recognition. His study looks at the relationship between Robot and fields such as Control theory, as well as how they intersect with chemical problems.

His Humanoid robot research incorporates themes from Control, Robot control and GRASP. Rüdiger Dillmann has researched Computer vision in several fields, including Interface, Movement and Mobile robot. When carried out as part of a general Human–computer interaction research project, his work on Augmented reality is frequently linked to work in Interface, therefore connecting diverse disciplines of study.

His most cited work include:

  • Incremental Learning of Tasks From User Demonstrations, Past Experiences, and Vocal Comments (124 citations)
  • Programming by demonstration: dual-arm manipulation tasks for humanoid robots (109 citations)
  • Using gesture and speech control for commanding a robot assistant (104 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Artificial intelligence, Robot, Computer vision, Human–computer interaction and Mobile robot. His Artificial intelligence research incorporates elements of Machine learning and Task. His work carried out in the field of Task brings together such families of science as Knowledge base and Knowledge representation and reasoning.

His Robot research integrates issues from Simulation and Sensor fusion. His study explores the link between Mobile robot and topics such as Control engineering that cross with problems in Control. His biological study spans a wide range of topics, including Context and Real-time computing.

He most often published in these fields:

  • Artificial intelligence (54.38%)
  • Robot (36.86%)
  • Computer vision (26.28%)

What were the highlights of his more recent work (between 2012-2019)?

  • Artificial intelligence (54.38%)
  • Computer vision (26.28%)
  • Robot (36.86%)

In recent papers he was focusing on the following fields of study:

Rüdiger Dillmann mainly investigates Artificial intelligence, Computer vision, Robot, Humanoid robot and Human–computer interaction. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Laparoscopic surgery and Pattern recognition. The various areas that Rüdiger Dillmann examines in his Computer vision study include Robot kinematics and Spatial relation.

He combines subjects such as Control engineering and Simulation with his study of Robot. His Humanoid robot research includes themes of Probabilistic logic, Robot control, Workspace, Haptic technology and Reinforcement learning. His Human–computer interaction study combines topics from a wide range of disciplines, such as Context awareness, Cognitive computer and Knowledge management.

Between 2012 and 2019, his most popular works were:

  • Learning From Humans (80 citations)
  • Robot placement based on reachability inversion (66 citations)
  • Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots (43 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Rüdiger Dillmann mostly deals with Robot, Artificial intelligence, Human–computer interaction, Humanoid robot and Computer vision. The concepts of his Robot study are interwoven with issues in Control engineering and Simulation. In his research, Rüdiger Dillmann undertakes multidisciplinary study on Artificial intelligence and Interface.

His studies deal with areas such as Context awareness and Knowledge management as well as Human–computer interaction. His research integrates issues of Thumb, Robot learning and Function in his study of Humanoid robot. His research in Computer vision intersects with topics in Workspace, Robot kinematics, Reachability and Trajectory.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

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

M. Pardowitz;S. Knoop;R. Dillmann;R.D. Zollner.
systems man and cybernetics (2007)

200 Citations

Using gesture and speech control for commanding a robot assistant

O. Rogalla;M. Ehrenmann;R. Zollner;R. Becher.
robot and human interactive communication (2002)

162 Citations

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

R. Zollner;T. Asfour;R. Dillmann.
intelligent robots and systems (2004)

152 Citations

Learning From Humans

Aude Gemma Billard;Sylvain Calinon;Rüdiger Dillmann.
Springer Handbook of Robotics, 2nd Ed. (2016)

122 Citations

Adaptive periodic movement control for the four legged walking machine BISAM

W. Ilg;J. Albiez;H. Jedele;K. Berns.
international conference on robotics and automation (1999)

113 Citations

Robot programming by demonstration (RPD): supporting the induction by human interaction

H. Friedrich;S. Münch;R. Dillmann;S. Bocionek.
Machine Learning (1996)

110 Citations

Towards Cognitive Robots: Building Hierarchical Task Representations of Manipulations from Human Demonstration

R. Zoliner;M. Pardowitz;S. Knoop;R. Dillmann.
international conference on robotics and automation (2005)

103 Citations

The Humanoid Robot ARMAR: Design and Control

T. Asfour;K. Berns;R. Dillmann.
ieee ras international conference on humanoid robots (2000)

103 Citations

Understanding users intention: programming fine manipulation tasks by demonstration

R. Zollner;O. Rogalla;R. Dillmann;M. Zollner.
intelligent robots and systems (2002)

92 Citations

Manipulability analysis

Nikolaus Vahrenkamp;Tamim Asfour;Giorgio Metta;Giulio Sandini.
ieee-ras international conference on humanoid robots (2012)

92 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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