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.
Modeling Variable Curvature Parallel Continuum Robots Using Euler Curves
In this paper, we propose and investigate a new approach to modeling variable curvature continuum robot sections, based on Euler spirals. Euler spirals, also termed Clothoids, or Cornu spirals, are those curves in which the curvature increases linearly with their arc length. In this work, Euler spirals are applied to the kinematic modeling of continuum robots for the first time. The approach was evaluated using the sections of numerous continuum robots, including two novel parallel continuum robots. Each robot consists of three parallel sections, each with three thin, long McKibben actuators. These sections are poorly modeled by the widely used constant curvature kinematic model. The constant curvature and Euler spiral models were compared and the Euler spiral method was seen to be a significantly better match for a wide range of configurations of the robot hardware.
- Award ID(s):
- Publication Date:
- NSF-PAR ID:
- Journal Name:
- 2019 International Conference on Robotics and Automation (ICRA)
- Page Range or eLocation-ID:
- 1679 to 1685
- Sponsoring Org:
- National Science Foundation
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