Optimal Cosserat-based deformation control for robotic manipulation of linear objects
Résumé
The robotic shape control of deformable linear
objects has garnered increasing interest within the robotics
community. Despite recent progress, the majority of shape control
approaches can be classified into two main groups: open-loop
control, which relies on physically realistic models to represent
the object, and closed-loop control, which employs less precise
models alongside visual data to compute commands. In this
work, we present a novel 3D shape control approach that
includes the physically realistic Cosserat model into a closed-
loop control framework, using vision feedback to rectify errors
in real-time. This approach capitalizes on the advantages of both
groups: the realism and precision provided by physics-based
models, and the rapid computation, therefore enabling real-time
correction of model errors, and robustness to elastic parameter
estimation inherent in vision-based approaches. This is achieved
by computing a deformation Jacobian derived from both the
Cosserat model and visual data. To demonstrate the effectiveness
of the method, we conduct a series of shape control experiments
where robots are tasked with deforming linear objects towards
a desired shape.
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