D-Index & Metrics Best Publications
Mechanical and Aerospace Engineering
Japan
2023
Electronics and Electrical Engineering
Japan
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Mechanical and Aerospace Engineering D-index 58 Citations 13,082 843 World Ranking 428 National Ranking 6
Electronics and Electrical Engineering D-index 58 Citations 13,343 865 World Ranking 1083 National Ranking 36
Computer Science D-index 58 Citations 13,254 808 World Ranking 2393 National Ranking 21

Research.com Recognitions

Awards & Achievements

2023 - Research.com Mechanical and Aerospace Engineering in Japan Leader Award

2023 - Research.com Electronics and Electrical Engineering in Japan Leader Award

2022 - Research.com Mechanical and Aerospace Engineering in Japan Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Mechanical engineering
  • Robot

Masayuki Inaba focuses on Humanoid robot, Robot, Artificial intelligence, Computer vision and Mobile robot. His Humanoid robot research is multidisciplinary, relying on both Motion planning, Motion control, Control engineering, Simulation and Robot control. The study incorporates disciplines such as Object, Systems design, Trajectory and Human–computer interaction in addition to Robot.

Masayuki Inaba interconnects Sequence and Task in the investigation of issues within Artificial intelligence. His studies deal with areas such as Development and Graph as well as Computer vision. His study in Mobile robot is interdisciplinary in nature, drawing from both Matching, Image sensor and Knowledge-based systems.

His most cited work include:

  • Learning by watching: extracting reusable task knowledge from visual observation of human performance (648 citations)
  • Dynamically-Stable Motion Planning for Humanoid Robots (246 citations)
  • Online generation of humanoid walking motion based on a fast generation method of motion pattern that follows desired ZMP (241 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Robot, Artificial intelligence, Humanoid robot, Computer vision and Simulation. His work carried out in the field of Robot brings together such families of science as Control theory and Human–computer interaction. His Artificial intelligence research integrates issues from Task and GRASP.

The various areas that Masayuki Inaba examines in his Humanoid robot study include Motion, Motion control, Control engineering, Robot kinematics and Trajectory. Computer vision and Tactile sensor are frequently intertwined in his study. His Simulation research is multidisciplinary, incorporating perspectives in Mechanism and Actuator.

He most often published in these fields:

  • Robot (53.96%)
  • Artificial intelligence (48.35%)
  • Humanoid robot (38.42%)

What were the highlights of his more recent work (between 2017-2021)?

  • Robot (53.96%)
  • Artificial intelligence (48.35%)
  • Computer vision (37.41%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Robot, Artificial intelligence, Computer vision, Humanoid robot and Control theory. His Robot research is multidisciplinary, incorporating elements of Motion, Task, Human–computer interaction, Simulation and Trajectory. Artificial intelligence is closely attributed to GRASP in his work.

His Proximity sensor research extends to Computer vision, which is thematically connected. The concepts of his Humanoid robot study are interwoven with issues in Control and Tendon. His work deals with themes such as Wrench and Thrust, which intersect with Control theory.

Between 2017 and 2021, his most popular works were:

  • 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)
  • The Exchange of Knowledge Using Cloud Robotics (19 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Mechanical engineering
  • Robot

Masayuki Inaba focuses on Robot, Artificial intelligence, Computer vision, Control theory and Humanoid robot. His Robot study integrates concerns from other disciplines, such as Affordance, Human–computer interaction, Task analysis, Transformation and Trajectory. Grippers is closely connected to GRASP in his research, which is encompassed under the umbrella topic of Artificial intelligence.

His studies in Computer vision integrate themes in fields like Proximity sensor and Assistive robot. The Control theory study combines topics in areas such as Cog, Motion planning and Thrust. In his work, Motor control and Field of view is strongly intertwined with Sight, which is a subfield of Humanoid robot.

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.

Best Publications

Learning by watching: extracting reusable task knowledge from visual observation of human performance

Y. Kuniyoshi;M. Inaba;H. Inoue.
international conference on robotics and automation (1994)

992 Citations

Dynamically-Stable Motion Planning for Humanoid Robots

James J. Kuffner;Satoshi Kagami;Koichi Nishiwaki;Masayuki Inaba.
Autonomous Robots (2002)

367 Citations

Motion Planning for Humanoid Robots

James Kuffner;James Kuffner;Koichi Nishiwaki;Satoshi Kagami;Masayuki Inaba.
Springer Tracts in Advanced Robotics (2005)

351 Citations

Online generation of humanoid walking motion based on a fast generation method of motion pattern that follows desired ZMP

K. Nishiwaki;S. Kagami;Y. Kuniyoshi;M. Inaba.
intelligent robots and systems (2002)

348 Citations

Visual navigation using view-sequenced route representation

Y. Matsumoto;M. Inaba;H. Inoue.
international conference on robotics and automation (1996)

334 Citations

Design and development of research platform for perception-action integration in humanoid robot: H6

K. Nishiwaki;T. Sugihara;S. Kagami;F. Kanehiro.
intelligent robots and systems (2000)

311 Citations

Footstep planning among obstacles for biped robots

J.J. Kuffner;K. Nishiwaki;S. Kagami;M. Inaba.
intelligent robots and systems (2001)

247 Citations

Dynamic walking pattern generation for a humanoid robot based on optimal gradient method

K. Nagasaka;H. Inoue;M. Inaba.
systems man and cybernetics (1999)

239 Citations

Robot vision system with a correlation chip for real-time tracking, optical flow and depth map generation

H. Inoue;T. Tachikawa;M. Inaba.
international conference on robotics and automation (1992)

224 Citations

An advanced musculoskeletal humanoid Kojiro

I. Mizuuchi;Y. Nakanishi;Y. Sodeyama;Y. Namiki.
ieee-ras international conference on humanoid robots (2007)

208 Citations

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