2018 - IEEE Robotics & Automation Award “For scientific and educational contributions to the mechanics of manipulation enabling real-world robot autonomy, and for leadership in robotics.”
2000 - IEEE Fellow For contributions to robotic manipulation and graduate education in robotics.
1992 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For lasting contributions to robotic manipulation in the areas of compliant force control, planning under uncertainty, the mechanics of pushing, and sensorless manipulation strategies.
His primary areas of study are Robot, Artificial intelligence, Control engineering, Control theory and Robotics. The various areas that Matthew T. Mason examines in his Robot study include Motion, Sequence and GRASP. His Artificial intelligence research is multidisciplinary, incorporating elements of Simple, Task and Position.
His Control theory study combines topics in areas such as Collision and Bounded function. His Robotics research incorporates themes from Variety, Kinematics and Conveyor belt. As a part of the same scientific family, Matthew T. Mason mostly works in the field of Simulation, focusing on Manipulator and, on occasion, Mobile manipulator and Mechanics.
Matthew T. Mason spends much of his time researching Robot, Artificial intelligence, Control theory, Object and Computer vision. Matthew T. Mason interconnects Control engineering, Task and GRASP in the investigation of issues within Robot. His work in Control engineering covers topics such as Simulation which are related to areas like Manipulator.
His studies deal with areas such as Engineering drawing and Human–computer interaction as well as Artificial intelligence. His work deals with themes such as Kinematics, Bounded function and Motion control, which intersect with Control theory. In his study, which falls under the umbrella issue of Object, Algorithm is strongly linked to Sequence.
Matthew T. Mason mainly focuses on Artificial intelligence, Computer vision, Object, Robot and Robot end effector. The Artificial intelligence study combines topics in areas such as GRASP and Nonlinear system. Matthew T. Mason has included themes like Motion and Bin in his Object study.
His Robot research integrates issues from Automation, Robustness, Control theory, Grippers and Entropy. His Control theory research is multidisciplinary, incorporating perspectives in Kinematics and Equations of motion. His Work research incorporates elements of Control engineering and Key.
His primary areas of investigation include Artificial intelligence, Robot, Object, Computer vision and GRASP. Matthew T. Mason integrates Artificial intelligence and Source area in his research. His biological study spans a wide range of topics, including Automation, Thread, Human–computer interaction, Grippers and Robustness.
His work in Human–computer interaction addresses issues such as Robotics, which are connected to fields such as Code and Variety. The concepts of his Object study are interwoven with issues in Sorting, Theoretical computer science and Task. As a member of one scientific family, he mostly works in the field of Computer vision, focusing on Robot end effector and, on occasion, Vacuum pressure and Mechanical engineering.
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.
Compliance and Force Control for Computer Controlled Manipulators
Matthew T. Mason.
systems man and cybernetics (1981)
Robot Hands and the Mechanics of Manipulation
Matthew T. Mason;J. Kenneth Salisbury.
Automatic Synthesis of Fine-Motion Strategies for Robots
Tomás Lozano-pérez;Matthew T. Mason;Russell H. Taylor.
The International Journal of Robotics Research (1984)
Robot Motion: Planning and Control
Michale Brady;John M. Hollerbach;Timothy L. Johnson;Matthew T. Mason.
An exploration of sensorless manipulation
M.A. Erdmann;M.T. Mason.
international conference on robotics and automation (1986)
Mechanics and planning of manipulator pushing operations
M T Mason.
The International Journal of Robotics Research (1986)
Mechanics of Robotic Manipulation
Matthew T. Mason.
Stable pushing: mechanics, controllability, and planning
Kevin M. Lynch;Matthew T. Mason.
The International Journal of Robotics Research (1996)
Two-Dimensional Rigid-Body Collisions With Friction
Yu Wang;Matthew T. Mason.
Journal of Applied Mechanics (1992)
Dynamic nonprehensile manipulation : controllability, planning and experiments
Kevin M. Lynch;Matthew T. Mason.
The International Journal of Robotics Research (1999)
Profile was last updated on December 6th, 2021.
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