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Title: Tractable and Intuitive Dynamic Model for Soft Robots via the Recursive Newton-Euler Algorithm
Because of the complex nature of soft robots, formulating dynamic models that are simple, efficient, and sufficiently accurate for simulation or control is a difficult task. This paper introduces an algorithm based on a recursive Newton-Euler (RNE) approach that enables an accurate and tractable lumped parameter dynamic model. This model scales linearly in computational complexity with the number of discrete segments. We validate this model by comparing it to actual hardware data from a three-joint continuum soft robot (with six degrees of freedom represented in a constant curvature kinematic model). The results show that this RNE-based model can be computed faster than real-time. We also show that with minimal system identification, a simulation performed using the dynamic model matches the real robot data with a median error of 3.15 degrees.  more » « less
Award ID(s):
2024792 1935312
NSF-PAR ID:
10388356
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
IEEE International Conference on Soft Robotics (RoboSoft)
Page Range / eLocation ID:
416 to 422
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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