A physics-informed, vision-based method to reconstruct all deformation modes in slender bodies
This addresses shape estimation in biology and soft robotics, but is incremental as it applies an existing theory to a specific domain.
The paper tackled the problem of estimating the full shape and six deformation modes of slender flexible bodies from camera measurements, using a physics-informed approach based on Cosserat rod theory. The result was an accurate method with less than 5 mm error, demonstrated on soft robot arms.
This paper is concerned with the problem of estimating (interpolating and smoothing) the shape (pose and the six modes of deformation) of a slender flexible body from multiple camera measurements. This problem is important in both biology, where slender, soft, and elastic structures are ubiquitously encountered across species, and in engineering, particularly in the area of soft robotics. The proposed mathematical formulation for shape estimation is physics-informed, based on the use of the special Cosserat rod theory whose equations encode slender body mechanics in the presence of bending, shearing, twisting and stretching. The approach is used to derive numerical algorithms which are experimentally demonstrated for fiber reinforced and cable-driven soft robot arms. These experimental demonstrations show that the methodology is accurate (<5 mm error, three times less than the arm diameter) and robust to noise and uncertainties.