What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Robot
Robot, Actuator, Control engineering, Control theory and Artificial intelligence are his primary areas of study.
His biological study spans a wide range of topics, including Simulation and Trajectory.
His Actuator research is multidisciplinary, incorporating perspectives in Work, Torque and Stiffness.
He combines subjects such as Electrical impedance, Human–robot interaction and Soft robotics with his study of Control engineering.
As a member of one scientific family, he mostly works in the field of Control theory, focusing on Motion control and, on occasion, Control system.
His research in Artificial intelligence intersects with topics in Human–computer interaction, Task and Computer vision.
His most cited work include:
- Variable impedance actuators: A review (561 citations)
- Design of HyQ – a hydraulically and electrically actuated quadruped robot: (413 citations)
- Control of pneumatic muscle actuators (377 citations)
What are the main themes of his work throughout his whole career to date?
Darwin G. Caldwell focuses on Robot, Artificial intelligence, Simulation, Control engineering and Control theory.
Darwin G. Caldwell focuses mostly in the field of Robot, narrowing it down to topics relating to Kinematics and, in certain cases, Workspace.
His Artificial intelligence research integrates issues from Machine learning, Human–computer interaction and Computer vision.
His Simulation research is multidisciplinary, relying on both Work, Teleoperation and Laser.
His Control engineering study integrates concerns from other disciplines, such as Grippers, Robot kinematics, Efficient energy use and Motion control.
His study in Actuator is interdisciplinary in nature, drawing from both Mechatronics, Mechanism and Stiffness.
He most often published in these fields:
- Robot (47.84%)
- Artificial intelligence (30.25%)
- Simulation (29.21%)
What were the highlights of his more recent work (between 2015-2020)?
- Robot (47.84%)
- Artificial intelligence (30.25%)
- Control engineering (28.91%)
In recent papers he was focusing on the following fields of study:
His main research concerns Robot, Artificial intelligence, Control engineering, Control theory and Simulation.
His Robot study combines topics from a wide range of disciplines, such as Kinematics, Task and Actuator.
His Actuator study deals with Exoskeleton intersecting with Back support and Human–computer interaction.
His work deals with themes such as Margin and Computer vision, which intersect with Artificial intelligence.
Within one scientific family, Darwin G. Caldwell focuses on topics pertaining to Grippers under Control engineering, and may sometimes address concerns connected to GRASP.
His work in Simulation tackles topics such as Laser which are related to areas like Biomedical engineering.
Between 2015 and 2020, his most popular works were:
- Variable Stiffness Actuators: Review on Design and Components (167 citations)
- WALK-MAN: A High-Performance Humanoid Platform for Realistic Environments (138 citations)
- Learning Physical Collaborative Robot Behaviors From Human Demonstrations (116 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Robot
The scientist’s investigation covers issues in Robot, Artificial intelligence, Control theory, Simulation and Torque.
The study incorporates disciplines such as Control engineering, Kinematics and Task in addition to Robot.
His research integrates issues of Margin, Human–computer interaction and Computer vision in his study of Artificial intelligence.
His Control theory study combines topics in areas such as Gait, Computation and Motion planning.
Darwin G. Caldwell interconnects Zero moment point, Control, Teleoperation and Effect of gait parameters on energetic cost in the investigation of issues within Simulation.
His Torque research includes elements of Electrical impedance, Mechanical engineering, Work and Actuator.
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.
