TY - GEN
T1 - A physics-informed, vision-based method to reconstruct all deformation modes in slender bodies
AU - Kim, Seung Hyun
AU - Chang, Heng Sheng
AU - Shih, Chia Hsien
AU - Uppalapati, Naveen Kumar
AU - Halder, Udit
AU - Krishnan, Girish
AU - Mehta, Prashant G.
AU - Gazzola, Mattia
N1 - This work was financially supported by ONR MURI (N00014-19-1-2373). ⇤Mechanical Science and Engineering, †Coordinated Science Laboratory, University of Illinois at Urbana-Champaign. ‡Corr.: [email protected]. https://github.com/GazzolaLab/BR2-vision-based-smoothing
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.1109/ICRA46639.2022.9811909
DO - 10.1109/ICRA46639.2022.9811909
M3 - Conference contribution
AN - SCOPUS:85128620922
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 4810
EP - 4817
BT - 2022 IEEE International Conference on Robotics and Automation, ICRA 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Conference on Robotics and Automation, ICRA 2022
Y2 - 23 May 2022 through 27 May 2022
ER -