What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Robot
- Control theory
His main research concerns Robot, Artificial intelligence, Control theory, Central pattern generator and Simulation.
His Robot research integrates issues from Control engineering, Gait and Crawling.
His work in the fields of Artificial intelligence, such as Robotics, Probabilistic logic and Humanoid robot, overlaps with other areas such as Simple.
His Control theory study combines topics in areas such as Signal and Motion control.
Auke Jan Ijspeert interconnects Artificial neural network, Connectionism, Evolutionary algorithm and Traveling wave in the investigation of issues within Central pattern generator.
His Exoskeleton study in the realm of Simulation interacts with subjects such as SIGNAL.
His most cited work include:
- 2008 Special Issue: Central pattern generators for locomotion control in animals and robots: A review (1292 citations)
- Dynamical movement primitives: Learning attractor models for motor behaviors (825 citations)
- From swimming to walking with a salamander robot driven by a spinal cord model. (757 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Robot, Artificial intelligence, Control theory, Simulation and Control engineering.
His study in Central pattern generator extends to Robot with its themes.
His work carried out in the field of Central pattern generator brings together such families of science as Artificial neural network and Neuroscience.
Auke Jan Ijspeert is interested in Robotics, which is a field of Artificial intelligence.
While the research belongs to areas of Control theory, Auke Jan Ijspeert spends his time largely on the problem of Humanoid robot, intersecting his research to questions surrounding Torque.
His research in Control theory intersects with topics in Work and Exoskeleton.
He most often published in these fields:
- Robot (42.92%)
- Artificial intelligence (32.92%)
- Control theory (28.12%)
What were the highlights of his more recent work (between 2015-2021)?
- Robot (42.92%)
- Control theory (28.12%)
- Artificial intelligence (32.92%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Robot, Control theory, Artificial intelligence, Control theory and Simulation.
His Robot research includes elements of Control engineering, Robustness, Sensory system and Human–computer interaction.
Auke Jan Ijspeert combines subjects such as Swing, Gait, Torso, Gait and Humanoid robot with his study of Control theory.
His Artificial intelligence research incorporates themes from Trajectory, Wearable computer and Computer vision.
His work deals with themes such as Linear equation, Motion control, Torque, Exoskeleton and Work, which intersect with Control theory.
His studies examine the connections between Neuroscience and genetics, as well as such issues in Central pattern generator, with regards to Animal locomotion.
Between 2015 and 2021, his most popular works were:
- Environmental Monitoring using Autonomous Vehicles: A Survey of Recent Searching Techniques (64 citations)
- Reverse-engineering the locomotion of a stem amniote (58 citations)
- JammJoint: A Variable Stiffness Device Based on Granular Jamming for Wearable Joint Support (51 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Robotics
Robot, Control theory, Artificial intelligence, Robotics and Simulation are his primary areas of study.
When carried out as part of a general Robot research project, his work on Robot locomotion is frequently linked to work in Jamming, therefore connecting diverse disciplines of study.
His studies deal with areas such as Gait, Humanoid robot, Torso and Mobile robot as well as Control theory.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Milestone and Cognitive science.
His Robotics research is multidisciplinary, relying on both State, Animal locomotion, Central pattern generator and Current.
His Simulation study incorporates themes from Motion planning, Probabilistic logic, Actuator, Stiffness and Trajectory.
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