Matthew T. Mason is affiliated with Carnegie Mellon University in the United States. Their research primarily focuses on robotics, with a significant concentration on manipulation and control.
The main fields of study in their research include Engineering and Computer Science. Within these domains, their work is particularly associated with subfields such as Control and Systems Engineering, Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence, and Mechanical Engineering.
The scientist's research topics cover a broad range of areas related to robotic manipulation and learning. Key topics include Robot Manipulation and Learning, Robotic Path Planning Algorithms, Robotic Mechanisms and Dynamics, Reinforcement Learning in Robotics, Teleoperation and Haptic Systems, Soft Robotics and Applications, and Dynamics and Control of Mechanical Systems.
Frequent collaborators in their work consist of Xianyi Cheng, Yifan Hou, Eric Huang, Zhenzhong Jia, and Sarvesh Patil.
Publication venues where Matthew T. Mason regularly contributes include arXiv (Cornell University), the 2022 International Conference on Robotics and Automation (ICRA), IEEE Robotics and Automation Letters, The International Journal of Robotics Research, and the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Notable recent papers authored by or co-authored with them include:
Matthew T. Mason has been recognized with several awards, including the IEEE Robotics & Automation Award in 2018 for contributions to mechanics of manipulation and robotics leadership. They were named an IEEE Fellow in 2000 for work in robotic manipulation and graduate education and have been a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) since 1992, acknowledging advancements in compliant force control, planning under uncertainty, mechanics of pushing, and sensorless manipulation strategies.
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