What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Programming language
His scientific interests lie mostly in Artificial intelligence, Computer vision, Robot, Humanoid robot and Motion planning.
His studies deal with areas such as Machine learning and GRASP as well as Artificial intelligence.
His Computer vision study combines topics from a wide range of disciplines, such as Actuator, Hidden Markov model and Tactile sensor.
His Robot research integrates issues from Motor control, Visual perception, Simulation and Human–computer interaction.
His study in Humanoid robot is interdisciplinary in nature, drawing from both Inverse kinematics, Motion control, Robot control, Robot kinematics and Robot end effector.
His Object research is multidisciplinary, incorporating perspectives in Representation and Medial axis.
His most cited work include:
- ARMAR-III: An Integrated Humanoid Platform for Sensory-Motor Control (326 citations)
- Teaching and learning of robot tasks via observation of human performance (258 citations)
- Design of the TUAT/Karlsruhe humanoid hand (180 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, Humanoid robot and Human–computer interaction.
His work on Artificial intelligence is being expanded to include thematically relevant topics such as GRASP.
His biological study spans a wide range of topics, including Control engineering and Simulation.
He works mostly in the field of Control engineering, limiting it down to concerns involving Task and, occasionally, Control.
Rüdiger Dillmann combines subjects such as Visualization and Inverse kinematics with his study of Computer vision.
The Humanoid robot study combines topics in areas such as Motion, Representation, Motion control, Visual perception and Visual servoing.
He most often published in these fields:
- Artificial intelligence (62.05%)
- Robot (41.57%)
- Computer vision (39.46%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (62.05%)
- Robot (41.57%)
- Spiking neural network (7.53%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Robot, Spiking neural network, Robotics and Computer vision.
His research brings together the fields of Event and Artificial intelligence.
His Robot research is multidisciplinary, incorporating elements of Control engineering, Motion, Robotic arm and Human–computer interaction.
His Spiking neural network research also works with subjects such as
- Learning rule together with Distributed computing and Wavefront,
- Deep learning and related Grippers, Stiffness and GRASP,
- Algorithm together with Focus and Semantic Web.
His studies in Robotics integrate themes in fields like Computational neuroscience, Robot control and Reinforcement learning.
His research in Computer vision intersects with topics in Soft tissue, Displacement and Motion planning.
Between 2015 and 2021, his most popular works were:
- Autonomous navigation for reconfigurable snake-like robots in challenging, unknown environments (22 citations)
- Towards a framework for end-to-end control of a simulated vehicle with spiking neural networks (20 citations)
- Neuromorphic Stereo Vision: A Survey of Bio-Inspired Sensors and Algorithms. (16 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Programming language
The scientist’s investigation covers issues in Artificial intelligence, Spiking neural network, Robot, Robotics and Computer vision.
His research integrates issues of Soft tissue and Position in his study of Artificial intelligence.
The study incorporates disciplines such as Neuromorphic engineering, Event and Correspondence problem in addition to Spiking neural network.
His work carried out in the field of Robot brings together such families of science as Scheme, Manipulator and Torque.
His work is dedicated to discovering how Computer vision, Motion planning are connected with Start point, Object, Robotic arm, Robot kinematics and Social robot and other disciplines.
The concepts of his Neurorobotics study are interwoven with issues in Robotic hand, GRASP, Field, Human–computer interaction and Motor primitives.
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