Title
Robust Model-Predictive Deformation Control of a Soft Object by Using a Flexible Continuum Robot
Abstract
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.
Year
DOI
Venue
2018
10.1109/IROS.2018.8593880
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Keywords
Field
DocType
robust model-predictive deformation control,soft object,flexible continuum robot,soft tissues,prediction horizon-based controller
Linear approximation,Computer vision,Control theory,Weighting,Jacobian matrix and determinant,Computer science,Robot end effector,Artificial intelligence,Deformation (mechanics),Robot,Estimator
Conference
ISSN
ISBN
Citations 
2153-0858
978-1-5386-8095-7
0
PageRank 
References 
Authors
0.34
21
5
Name
Order
Citations
PageRank
Bo Ouyang100.34
Hangjie Mo201.35
Haoyao Chen318923.79
Liu YH41540185.05
Dong Sun596687.31