What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Geometry
The scientist’s investigation covers issues in Visual servoing, Computer vision, Artificial intelligence, Robot and Robustness.
His work carried out in the field of Visual servoing brings together such families of science as Motion, Stability, Control theory, Task and Motion control.
His Control theory study incorporates themes from Camera resectioning and Rotation.
He has included themes like Mobile robot navigation, Robotics and Position in his Computer vision study.
As part of one scientific family, François Chaumette deals mainly with the area of Robot, narrowing it down to issues related to the Control engineering, and often Servo control.
The Robust control research François Chaumette does as part of his general Robustness study is frequently linked to other disciplines of science, such as Homography, therefore creating a link between diverse domains of science.
His most cited work include:
- Visual servo control. I. Basic approaches (1582 citations)
- A new approach to visual servoing in robotics (1378 citations)
- 2 1/2 D visual servoing (802 citations)
What are the main themes of his work throughout his whole career to date?
François Chaumette spends much of his time researching Artificial intelligence, Computer vision, Visual servoing, Robot and Robustness.
His is involved in several facets of Artificial intelligence study, as is seen by his studies on Robotics, Robot control, Active vision, Pose and Robot end effector.
His work deals with themes such as Robot kinematics and Mobile robot, which intersect with Computer vision.
The Visual servoing study combines topics in areas such as Trajectory, Control theory, Task, Motion control and Position.
François Chaumette combines subjects such as Control engineering and Control theory with his study of Robot.
His Robustness research is multidisciplinary, relying on both Augmented reality, Exponential stability, Eye tracking and Monocular vision.
He most often published in these fields:
- Artificial intelligence (83.01%)
- Computer vision (80.45%)
- Visual servoing (75.00%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (83.01%)
- Computer vision (80.45%)
- Visual servoing (75.00%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Visual servoing, Robot and Robustness.
François Chaumette interconnects Visualization and Mobile robot in the investigation of issues within Computer vision.
His Visual servoing research includes themes of Robotics, Parallel manipulator, Pose and Visual control.
His studies deal with areas such as Automation and Simultaneous localization and mapping as well as Robotics.
His Robot research is multidisciplinary, incorporating elements of Artificial neural network, Control theory, Trajectory and Convolutional neural network.
The various areas that François Chaumette examines in his Robustness study include Stability, Deep learning and Acoustic source localization.
Between 2014 and 2021, his most popular works were:
- RemoveDEBRIS: An in-orbit active debris removal demonstration mission (67 citations)
- Training Deep Neural Networks for Visual Servoing (46 citations)
- A visual servoing approach for autonomous corridor following and doorway passing in a wheelchair (41 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Geometry
François Chaumette mainly focuses on Visual servoing, Artificial intelligence, Computer vision, Robot and Control theory.
His research in Visual servoing intersects with topics in Visual control, Task, Motion control, Humanoid robot and Rate of convergence.
His work on Motion and Adaptive control as part of general Artificial intelligence study is frequently connected to Synthetic vision system and Character animation, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His work on Image moment and Optical flow as part of general Computer vision study is frequently linked to Focus and Set, bridging the gap between disciplines.
His Robot research integrates issues from Artificial neural network, Line segment and Convolutional neural network.
His work in the fields of Control theory, such as Trajectory, Robustness and Kalman filter, intersects with other areas such as Property.
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.
