What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Electrical engineering
His primary areas of study are Robot, Modular design, Self-reconfiguring modular robot, Control engineering and Actuator.
His Robot research incorporates elements of Graph, Simulation and Theoretical computer science.
His Modular design research is multidisciplinary, incorporating elements of Software, Robustness and Mobile robot.
Mark Yim interconnects Embedded system, Robotics, Control reconfiguration and Motion planning in the investigation of issues within Self-reconfiguring modular robot.
Mark Yim usually deals with Control engineering and limits it to topics linked to Systems engineering and Robotic systems.
His work deals with themes such as Control unit, Mechanism, Position sensor and Computer hardware, which intersect with Actuator.
His most cited work include:
- Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics] (670 citations)
- PolyBot: a modular reconfigurable robot (546 citations)
- Tactile feedback man-machine interface device (531 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Robot, Modular design, Self-reconfiguring modular robot, Control engineering and Actuator.
His Robot study is related to the wider topic of Artificial intelligence.
His biological study spans a wide range of topics, including Robotics, Motion planning, Control theory, Embedded system and Robot control.
His studies deal with areas such as Distributed computing, Task, Human–computer interaction, Algorithm and Robustness as well as Self-reconfiguring modular robot.
His studies in Actuator integrate themes in fields like Mechanical engineering and Computer hardware.
His work carried out in the field of Simulation brings together such families of science as Mechanism and Robot end effector.
He most often published in these fields:
- Robot (45.02%)
- Modular design (39.84%)
- Self-reconfiguring modular robot (27.09%)
What were the highlights of his more recent work (between 2017-2021)?
- Robot (45.02%)
- Modular design (39.84%)
- Self-reconfiguring modular robot (27.09%)
In recent papers he was focusing on the following fields of study:
Mark Yim spends much of his time researching Robot, Modular design, Self-reconfiguring modular robot, Artificial intelligence and Control theory.
Mark Yim works in the field of Robot, namely Motion planning.
His Modular design study combines topics in areas such as Control engineering, Control theory, Propulsion and Robot control.
Manipulator, Robot end effector, GRASP and Workspace is closely connected to Computer vision in his research, which is encompassed under the umbrella topic of Artificial intelligence.
The concepts of his Control theory study are interwoven with issues in Blade pitch and Rotor.
His Truss research is multidisciplinary, incorporating perspectives in Control reconfiguration, Topology and Actuator.
Between 2017 and 2021, his most popular works were:
- ModQuad: The Flying Modular Structure that Self-Assembles in Midair (33 citations)
- An integrated system for perception-driven autonomy with modular robots (25 citations)
- Modular Reconfigurable Robotics (19 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Electrical engineering
His main research concerns Robot, Modular design, Self-reconfiguring modular robot, Task and Human–computer interaction.
His work on Robotic systems as part of general Robot research is frequently linked to Socialization, thereby connecting diverse disciplines of science.
His Modular design research is multidisciplinary, relying on both Computer hardware, Cuboid, Control reconfiguration, Artificial intelligence and Robot kinematics.
His Artificial intelligence study incorporates themes from State and Systems engineering.
His Robot kinematics research incorporates themes from Control engineering, Control theory and Pose.
His Self-reconfiguring modular robot research entails a greater understanding of Robot control.
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