2012 - IEEE Fellow For contributions to robot programming and human-centerd technologies
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 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.
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.
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.
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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)
Using gesture and speech control for commanding a robot assistant
O. Rogalla;M. Ehrenmann;R. Zollner;R. Becher.
robot and human interactive communication (2002)
Programming by demonstration: dual-arm manipulation tasks for humanoid robots
R. Zollner;T. Asfour;R. Dillmann.
intelligent robots and systems (2004)
Learning From Humans
Aude Gemma Billard;Sylvain Calinon;Rüdiger Dillmann.
Springer Handbook of Robotics, 2nd Ed. (2016)
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)
Robot programming by demonstration (RPD): supporting the induction by human interaction
H. Friedrich;S. Münch;R. Dillmann;S. Bocionek.
Machine Learning (1996)
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)
The Humanoid Robot ARMAR: Design and Control
T. Asfour;K. Berns;R. Dillmann.
ieee ras international conference on humanoid robots (2000)
Understanding users intention: programming fine manipulation tasks by demonstration
R. Zollner;O. Rogalla;R. Dillmann;M. Zollner.
intelligent robots and systems (2002)
Nikolaus Vahrenkamp;Tamim Asfour;Giorgio Metta;Giulio Sandini.
ieee-ras international conference on humanoid robots (2012)
Profile was last updated on December 6th, 2021.
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