What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Control theory
His scientific interests lie mostly in Control theory, Humanoid robot, Artificial intelligence, Control engineering and Robot.
His Control theory study integrates concerns from other disciplines, such as Kinematics, Robot kinematics, Motion planning and Nonholonomic system.
His studies deal with areas such as Underactuation, Motion control, Simulation and Robot control, Social robot as well as Humanoid robot.
His research links Computer vision with Artificial intelligence.
His Control engineering study combines topics in areas such as Stability, Robot manipulator, Actuator, Equations of motion and Manipulator kinematics.
His Robot research is multidisciplinary, relying on both Work and Forceps.
His most cited work include:
- Advanced Robotics: Redundancy and Optimization (909 citations)
- Inverse kinematic solutions with singularity robustness for robot manipulator control (860 citations)
- Real-time humanoid motion generation through ZMP manipulation based on inverted pendulum control (419 citations)
What are the main themes of his work throughout his whole career to date?
Yoshihiko Nakamura spends much of his time researching Artificial intelligence, Control theory, Humanoid robot, Computer vision and Robot.
Motion, Motion capture, Hidden Markov model, Robotics and Motion estimation are subfields of Artificial intelligence in which his conducts study.
His Control theory research incorporates elements of Control engineering, Kinematics, Robot kinematics and Nonholonomic system.
His Control engineering research includes themes of Mechanism and Robot control.
His Humanoid robot study combines topics from a wide range of disciplines, such as Mobile robot, Motion control, Actuator, Simulation and Trajectory.
His research in Computer vision intersects with topics in Visualization and Inverse kinematics.
He most often published in these fields:
- Artificial intelligence (38.26%)
- Control theory (29.57%)
- Humanoid robot (29.22%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (38.26%)
- Computer vision (23.48%)
- Humanoid robot (29.22%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Humanoid robot, Motion and Robot.
Yoshihiko Nakamura regularly ties together related areas like Field in his Artificial intelligence studies.
His Computer vision study incorporates themes from Simultaneous localization and mapping and Inverse kinematics.
His Humanoid robot research is multidisciplinary, incorporating elements of Simulation and Actuator, Torque, Control theory.
He works mostly in the field of Control theory, limiting it down to concerns involving Viscoelasticity and, occasionally, Hydraulic cylinder.
His Robot research also works with subjects such as
- Kinematics and related Trajectory,
- Contact force most often made with reference to Hidden Markov model.
Between 2015 and 2021, his most popular works were:
- ZMP Support Areas for Multicontact Mobility Under Frictional Constraints (51 citations)
- Mechanism and Control of Whole-Body Electro-Hydrostatic Actuator Driven Humanoid Robot Hydra (24 citations)
- Modeling and Identification of a Realistic Spiking Neural Network and Musculoskeletal Model of the Human Arm, and an Application to the Stretch Reflex (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Computer vision
Yoshihiko Nakamura mostly deals with Artificial intelligence, Computer vision, Humanoid robot, Robot and Motion.
His study in Motion capture, Robotics and Inverse kinematics falls within the category of Artificial intelligence.
His Computer vision research integrates issues from Hidden Markov model and Benchmark.
The concepts of his Humanoid robot study are interwoven with issues in Trochoid, Stability, Actuator, Control theory and Simulation.
His research integrates issues of Bipedalism and Ellipsoid in his study of Control theory.
His Robot research includes themes of Context and Kinematics.
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