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- W2284990594 abstract "In hands-on robotic surgery, the surgical tool is mounted on the end-effector of a robot and is directly manipulated by the surgeon. This simultaneously exploits the strengths of both humans and robots, such that the surgeon directly feels tool-tissue interactions and remains in control of the procedure, while taking advantage of the robot's higher precision and accuracy. A crucial challenge in hands-on robotics for delicate manipulation tasks, such as surgery, is that the user must interact with the dynamics of the robot at the end-effector, which can reduce dexterity and increase fatigue. This paper presents a null-space-based optimization technique for simultaneously minimizing the mass and friction of the robot that is experienced by the surgeon. By defining a novel optimization technique for minimizing the projection of the joint friction onto the end-effector, and integrating this with our previous techniques for minimizing the belted mass/inertia as perceived by the hand, a significant reduction in dynamics felt by the user is achieved. Experimental analyses in both simulation and human user trials demonstrate that the presented method can reduce the user-experienced dynamic mass and friction by, on average, 44% and 41%, respectively. The results presented robustly demonstrate that optimizing a robots pose can result in a more natural tool motion, potentially allowing future surgical robots to operate with increased usability, improved surgical outcomes, and wider clinical uptake." @default.
- W2284990594 created "2016-06-24" @default.
- W2284990594 creator A5008455248 @default.
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- W2284990594 date "2016-02-01" @default.
- W2284990594 modified "2023-09-26" @default.
- W2284990594 title "Mass and Friction Optimization for Natural Motion in Hands-On Robotic Surgery" @default.
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- W2284990594 doi "https://doi.org/10.1109/tro.2015.2507163" @default.
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