Her main research concerns Artificial intelligence, Robot, Humanoid robot, Imitation and Robot learning. She has included themes like Task and Computer vision in her Artificial intelligence study. Aude Billard interconnects Context and Human–computer interaction in the investigation of issues within Robot.
Her Humanoid robot research incorporates elements of Motion, Machine learning, Simulation and Hidden Markov model. Her biological study spans a wide range of topics, including Metric, Developmental psychology, Autism, Cognitive science and Set. Her studies deal with areas such as Reinforcement learning and Social robot as well as Robot learning.
Her primary areas of study are Artificial intelligence, Robot, Computer vision, Humanoid robot and Human–computer interaction. The Artificial intelligence study combines topics in areas such as Imitation and Task. Her research in Imitation intersects with topics in Artificial neural network, Cognitive science, Gesture and Set.
The study incorporates disciplines such as Dynamical systems theory, Control theory and Simulation in addition to Robot. The concepts of her Computer vision study are interwoven with issues in Kinematics and GRASP. Her Humanoid robot research includes elements of Developmental psychology, Autism, Machine learning and Hidden Markov model.
Aude Billard focuses on Robot, Artificial intelligence, Dynamical systems theory, Human–computer interaction and Task. Her Robot research is multidisciplinary, relying on both Motion and Control theory. Aude Billard works on Artificial intelligence which deals in particular with Robotics.
Her research integrates issues of Dynamical system, Control engineering, Stability and Motion planning in her study of Dynamical systems theory. Her Human–computer interaction research is multidisciplinary, incorporating perspectives in Kinematics, Action, Cognition, Brain–computer interface and Adaptive control. Her studies deal with areas such as Machine learning, Deep learning and Pipeline as well as Task.
The scientist’s investigation covers issues in Robot, Artificial intelligence, Dynamical systems theory, Task and Dynamical system. Her work in Robot covers topics such as Control theory which are related to areas like Obstacle avoidance and Hull. Her research in Artificial intelligence intersects with topics in Electromyography, Computer vision and GRASP.
The Dynamical systems theory study combines topics in areas such as Stability, Motion planning and Robot manipulator. Her work carried out in the field of Task brings together such families of science as Control engineering, Machine learning, Deep learning and Handwriting. Aude Billard interconnects Point, Robot kinematics and Classical mechanics, Impact in the investigation of issues within Dynamical system.
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On Learning, Representing, and Generalizing a Task in a Humanoid Robot
S. Calinon;F. Guenter;A. Billard.
systems man and cybernetics (2007)
Robotic assistants in therapy and education of children with autism: can a small humanoid robot help encourage social interaction skills?
B. Robins;K. Dautenhahn;Te Boekhorst;A. Billard.
Universal Access in The Information Society (2005)
Computational approaches to motor learning by imitation
Stefan Schaal;Auke Ijspeert;Aude Billard;Aude Billard.
Philosophical Transactions of the Royal Society B (2003)
Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models
S. M. Khansari-Zadeh;A. Billard.
IEEE Transactions on Robotics (2011)
From Animals to Animats
S. Schaal;A.J. Ijspeert;A Billard;S. Vijayakumar.
simulation of adaptive behavior (2004)
Learning and Reproduction of Gestures by Imitation
Sylvain Calinon;Florent D'halluin;Eric L Sauser;Darwin G Caldwell.
IEEE Robotics & Automation Magazine (2010)
Incremental learning of gestures by imitation in a humanoid robot
Sylvain Calinon;Aude Billard.
human-robot interaction (2007)
A survey of Tactile Human-Robot Interactions
Brenna D. Argall;Aude G. Billard.
Robotics and Autonomous Systems (2010)
Synthetic brain imaging: grasping, mirror neurons and imitation
M. A. Arbib;A. Billard;M. Iacoboni;E. Oztop.
Neural Networks (2000)
Learning human arm movements by imitation:: Evaluation of a biologically inspired connectionist architecture
Aude Billard;Maja J. Matarić.
Robotics and Autonomous Systems (2001)
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