What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Robot
- Mechanical engineering
His primary areas of investigation include Robot, Humanoid robot, Simulation, Artificial intelligence and Control theory.
His Mobile robot, Robot locomotion and Motion planning study in the realm of Robot connects with subjects such as Control methods.
His Humanoid robot study combines topics in areas such as Motion, Human–robot interaction, Robot control, Social robot and Robot kinematics.
His Simulation research includes elements of Preferred walking speed, Mechanism, Trajectory and Motion control.
Atsuo Takanishi has included themes like Emotional expression, Human–computer interaction and Computer vision in his Artificial intelligence study.
His Control theory research is multidisciplinary, incorporating elements of Zero moment point and Stairs.
His most cited work include:
- Development of a bipedal humanoid robot-control method of whole body cooperative dynamic biped walking (336 citations)
- The Realization of Dynamic Walking by the Biped Walking Robot WL-10 RD (225 citations)
- Development of a Biped Walking Robot Compensating for Three-Axis Moment by Trunk Motion (167 citations)
What are the main themes of his work throughout his whole career to date?
Atsuo Takanishi mainly investigates Robot, Humanoid robot, Simulation, Artificial intelligence and Computer vision.
The Robot study combines topics in areas such as Mechanism, Human–computer interaction and Control theory.
In the subject of general Control theory, his work in Actuator, Trajectory and Compensation is often linked to Trunk, thereby combining diverse domains of study.
His research in Humanoid robot tackles topics such as Social robot which are related to areas like Robot learning.
In his work, Training system is strongly intertwined with Task, which is a subfield of Simulation.
His Artificial intelligence study frequently links to adjacent areas such as Motor control.
He most often published in these fields:
- Robot (63.71%)
- Humanoid robot (39.78%)
- Simulation (37.37%)
What were the highlights of his more recent work (between 2015-2021)?
- Robot (63.71%)
- Artificial intelligence (36.16%)
- Simulation (37.37%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Robot, Artificial intelligence, Simulation, Control theory and Computer vision.
His work on Humanoid robot as part of general Robot research is often related to Disaster response, thus linking different fields of science.
Atsuo Takanishi focuses mostly in the field of Humanoid robot, narrowing it down to topics relating to Joint stiffness and, in certain cases, Ankle.
Atsuo Takanishi works mostly in the field of Simulation, limiting it down to topics relating to Climbing and, in certain cases, Quadrupedalism, as a part of the same area of interest.
Atsuo Takanishi interconnects Robot kinematics and Motion planning in the investigation of issues within Control theory.
His Computer vision research incorporates elements of Torso and Legged robot.
Between 2015 and 2021, his most popular works were:
- Material recognition CNNs and hierarchical planning for biped robot locomotion on slippery terrain (29 citations)
- Footstep Planning for Slippery and Slanted Terrain Using Human-Inspired Models (26 citations)
- A Modified Robotic Rat to Study Rat-Like Pitch and Yaw Movements (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, Simulation, Humanoid robot, Artificial intelligence and Control theory.
His Robot study incorporates themes from Actuator, Trajectory and Climbing.
His Simulation research includes themes of Crawling, Gait, Inverse kinematics, Legged robot and Robot end effector.
His Humanoid robot study combines topics from a wide range of disciplines, such as Robotics, Robot control, Perception and Human–computer interaction.
His research investigates the connection between Artificial intelligence and topics such as Computer vision that intersect with issues in Robustness and Data mining.
His work carried out in the field of Control theory brings together such families of science as Mechanism, Robot kinematics and Motion planning.
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.
