What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Operating system
Kei Okada mostly deals with Humanoid robot, Robot, Artificial intelligence, Motion planning and Computer vision.
His study in Humanoid robot is interdisciplinary in nature, drawing from both Software system, Control engineering, Simulation, Robot control and Robot kinematics.
Mobile robot is the focus of his Robot research.
In his study, Inverse kinematics is strongly linked to Graph, which falls under the umbrella field of Artificial intelligence.
In his research on the topic of Motion planning, Autonomous robot, Robotics and Robot learning is strongly related with Task.
His work carried out in the field of Computer vision brings together such families of science as Probabilistic logic and Computer graphics.
His most cited work include:
- Charged-particle multiplicity measurement in proton-proton collisions at $\sqrt{s}=7$ TeV with ALICE at LHC (236 citations)
- Analysis and Observations From the First Amazon Picking Challenge (196 citations)
- Alignment of the ALICE Inner Tracking System with cosmic-ray tracks (178 citations)
What are the main themes of his work throughout his whole career to date?
Kei Okada spends much of his time researching Artificial intelligence, Robot, Computer vision, Humanoid robot and Simulation.
His Artificial intelligence research integrates issues from Task and GRASP.
The various areas that Kei Okada examines in his Robot study include Human–computer interaction and Control theory.
His is involved in several facets of Computer vision study, as is seen by his studies on Segmentation, Stereo cameras and Machine vision.
His Humanoid robot research is multidisciplinary, incorporating elements of Motion planning, Motion control, Control engineering, Actuator and Trajectory.
His research on Simulation often connects related topics like Mechanism.
He most often published in these fields:
- Artificial intelligence (43.86%)
- Robot (41.81%)
- Computer vision (36.01%)
What were the highlights of his more recent work (between 2017-2021)?
- Robot (41.81%)
- Artificial intelligence (43.86%)
- Humanoid robot (34.47%)
In recent papers he was focusing on the following fields of study:
Kei Okada mainly focuses on Robot, Artificial intelligence, Humanoid robot, Computer vision and Control theory.
His biological study spans a wide range of topics, including Motion, Task, Human–computer interaction, Simulation and Trajectory.
As a part of the same scientific family, Kei Okada mostly works in the field of Artificial intelligence, focusing on GRASP and, on occasion, Grippers.
His Humanoid robot study which covers Control that intersects with State and Control system.
Computer vision and Proximity sensor are frequently intertwined in his study.
His Control theory study integrates concerns from other disciplines, such as Wrench and Thrust.
Between 2017 and 2021, his most popular works were:
- Analysis and Observations From the First Amazon Picking Challenge (196 citations)
- Design, Modeling, and Control of an Aerial Robot DRAGON: A Dual-Rotor-Embedded Multilink Robot With the Ability of Multi-Degree-of-Freedom Aerial Transformation (49 citations)
- Transformable multirotor with two-dimensional multilinks: Modeling, control, and whole-body aerial manipulation: (20 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Robot
His primary areas of study are Robot, Artificial intelligence, Computer vision, Control theory and Humanoid robot.
Kei Okada interconnects Wrench, Task analysis and Human–computer interaction in the investigation of issues within Robot.
Kei Okada focuses mostly in the field of Artificial intelligence, narrowing it down to matters related to GRASP and, in some cases, Grippers.
His research investigates the link between Computer vision and topics such as Proximity sensor that cross with problems in Assistive robot and Suction.
He has researched Control theory in several fields, including Cog, Motion planning and Thrust.
His work investigates the relationship between Humanoid robot and topics such as Sight that intersect with problems in Motor control and Field of view.
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