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Title: Real-time Dynamic Models for Soft Bending Actuators
Soft robotics has witnessed increased attention from the robotic community due to their desirable features in compliant manipulation in unstructured spaces and human-friendly applications. Their light-weight designs and low-stiffness are ideally suited for environments with fragile and sensitive objects without causing damage. Deformation sensing of soft robots so far has relied on highly nonlinear bending sensors and vision-based methods that are not suitable for obtaining precise and reliable state feedback. In this work, for the first time, we explore the use of a state-of-the-art high fidelity deformation sensor that is based on optical frequency domain reflcctometry in soft bending actuators. These sensors are capable of providing spatial coordinate feedback along the length of the sensor at every 0.8 mm at up to 250 Hz. This work systematically analyzes the sensor feedback for soft bending actuator deformation and then introduces a reduced order kinematic model, together with cubic spline interpolation, which could be used to reconstruct the continuous deformation of the soft bending actuators. The kinematic model is then extended to derive an efficient dynamic model which runs at 1.5 kHz and validated against the experimental data.
Authors:
; ; ; ; ;
Award ID(s):
1718755
Publication Date:
NSF-PAR ID:
10109161
Journal Name:
2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)
Page Range or eLocation-ID:
1310 to 1315
Sponsoring Org:
National Science Foundation
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