PROJECT TITLE :

Automatic 3-D Manipulation of Soft Objects by Robotic Arms With an Adaptive Deformation Model

ABSTRACT:

In this paper, we gift a brand new feedback method to automatically servo-control the 3-D shape of sentimental objects with robotic manipulators. The soft object manipulation downside has recently received a great deal of attention from robotics researchers as a result of of its potential applications in, e.g., food industry, home robots, medical robotics, and manufacturing. A serious complication to automatically management the shape of an object is that the estimation of its deformation properties, which determines how the manipulator's motion actively transforms into deformations. Note that these properties are rarely known beforehand, and its offline parametric identification is tough and/or impractical to conduct in many applications. To deal with this issue, we developed a brand new algorithm that computes in real time the unknown deformation parameters of a soft object; this algorithm provides a valuable adaptive behavior to the deformation controller, one thing we tend to cannot achieve with traditional fastened-model approaches. In distinction with most controllers in the literature, our new technique can explicitly servo-management three-D deformations (and not just 2-D image projections) in an entirely model-free approach. To validate the proposed adaptive controller, we gift a close experimental study with robotic manipulators.


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