What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Surgery
- Mechanical engineering
Mamoru Mitsuishi focuses on Simulation, Machining, Haptic technology, Mechanical engineering and Telerobotics.
His studies in Simulation integrate themes in fields like User interface, Task, Motion control, Master/slave and Contact force.
His study on Motion control also encompasses disciplines like
- Control theory together with Artificial neural network, Catastrophic failure, Actuator and Deformation,
- Control theory and related Focus,
- Navigation system which intersects with area such as Robot.
His Machining research incorporates themes from Cortical bone, Biomedical engineering and Thermal deformation.
His Haptic technology research includes themes of Forceps and Compensation.
His studies deal with areas such as Indentation, Structural engineering and Torque as well as Mechanical engineering.
His most cited work include:
- Biomedical production of implants by additive electro-chemical and physical processes (194 citations)
- Open Controller Architecture – Past, Present and Future (177 citations)
- GestureMan: a mobile robot that embodies a remote instructor's actions (107 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Simulation, Computer vision, Robot and Machining.
He works on Simulation which deals in particular with Haptic technology.
His Haptic technology research integrates issues from Forceps and Control theory.
Mamoru Mitsuishi focuses mostly in the field of Computer vision, narrowing it down to matters related to Ultrasound and, in some cases, Biomedical engineering and Match moving.
His Robot research incorporates elements of Orthopedic surgery, Surgery and Cutting tool.
His research integrates issues of Control engineering and Machine tool in his study of Machining.
He most often published in these fields:
- Artificial intelligence (21.64%)
- Simulation (20.90%)
- Computer vision (17.41%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (21.64%)
- Computer vision (17.41%)
- Robot (14.43%)
In recent papers he was focusing on the following fields of study:
Mamoru Mitsuishi mostly deals with Artificial intelligence, Computer vision, Robot, Optics and Simulation.
His Artificial intelligence study combines topics in areas such as Machine learning and Task.
His Task study combines topics from a wide range of disciplines, such as Automation, Data set and Process.
His research in Computer vision tackles topics such as Imaging phantom which are related to areas like High-intensity focused ultrasound.
His Robot research is multidisciplinary, relying on both Intelligent control, Constraint, Surgery and Task.
His work on Haptic technology as part of his general Simulation study is frequently connected to Ilm peeling, thereby bridging the divide between different branches of science.
Between 2015 and 2021, his most popular works were:
- High-efficiency and precision cutting of glass by selective laser-assisted milling (35 citations)
- Online Trajectory Planning and Force Control for Automation of Surgical Tasks (31 citations)
- Laser-assisted Machining of Zirconia Ceramics using a Diamond Bur (24 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Surgery
- Mechanical engineering
Mamoru Mitsuishi mainly investigates Optics, Simulation, Interferometry, Wavelength and Robot.
He studies Simulation, focusing on Haptic technology in particular.
In the field of Interferometry, his study on Fizeau interferometer overlaps with subjects such as Characteristic polynomial.
His research in Wavelength intersects with topics in Surface finish, Cutting tool, Brittleness, Laser assisted and Coating.
His study in Robot is interdisciplinary in nature, drawing from both Da Vinci Surgical System, Surgery, Collision avoidance and Robotic arm.
His research in Control engineering focuses on subjects like Reinforcement learning, which are connected to Contact force.
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