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Robust Model-Predictive Deformation Control of a Soft Object by Using a Flexible Continuum Robot

Bo Ouyang, Hangjie Mo, Haoyao Chen, Yunhui Liu, Dong Sun

发表年份
2018
引用次数
20

摘要

Flexible continuum robots have exhibited unique advantages in working in an unstructured environment. Many applications require robots to actively control the deformation of soft objects, such as soft tissues in surgery. Thus, this study presents a robust model-predictive deformation control of a soft object using a flexible continuum robot. A linear approximation model for mapping from actuation space of a continuum robot to deformation space of a soft object is established. Jacobian matrix is estimated online by using a robust Geman-McClure estimator. Then, the deformation of the soft object is regulated by using a prediction horizon-based controller with exponential weighting for model uncertainty. The proposed control approach is effective in manipulating a soft object with a flexible continuum robot that is in contact with obstacles.

关键词

RobotJacobian matrix and determinantWeightingComputer scienceControl theory (sociology)Artificial intelligenceSoft roboticsComputer visionRobust controlControl system

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