Soft Robotics Education

Soft Robotics ◽  
2014 ◽  
Vol 1 (3) ◽  
pp. 202-212 ◽  
Author(s):  
Xiaoxiang Yu ◽  
Surya Girinatha Nurzaman ◽  
Utku Culha ◽  
Fumiya Iida
Soft Robotics ◽  
2014 ◽  
Vol 1 (2) ◽  
pp. 147-153 ◽  
Author(s):  
Dino Rossi ◽  
Zoltán Nagy ◽  
Arno Schlueter

Robotica ◽  
2021 ◽  
pp. 1-31
Author(s):  
Andrew Spielberg ◽  
Tao Du ◽  
Yuanming Hu ◽  
Daniela Rus ◽  
Wojciech Matusik

Abstract We present extensions to ChainQueen, an open source, fully differentiable material point method simulator for soft robotics. Previous work established ChainQueen as a powerful tool for inference, control, and co-design for soft robotics. We detail enhancements to ChainQueen, allowing for more efficient simulation and optimization and expressive co-optimization over material properties and geometric parameters. We package our simulator extensions in an easy-to-use, modular application programming interface (API) with predefined observation models, controllers, actuators, optimizers, and geometric processing tools, making it simple to prototype complex experiments in 50 lines or fewer. We demonstrate the power of our simulator extensions in over nine simulated experiments.


Small Science ◽  
2021 ◽  
pp. 2100002
Author(s):  
Tomohito Sekine ◽  
Yi-Fei Wang ◽  
Jinseo Hong ◽  
Yasunori Takeda ◽  
Reo Miura ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4130
Author(s):  
Eric Rasmussen ◽  
Daniel Guo ◽  
Vybhav Murthy ◽  
Rachit Mishra ◽  
Cameron Riviere ◽  
...  

The field of soft robotics has attracted the interest of the medical community due to the ability of soft elastic materials to traverse the abnormal environment of the human body. However, sensing in soft robotics has been challenging due to the sensitivity of soft sensors to various loading conditions and the nonlinear signal responses that can arise under extreme loads. Ideally, soft sensors should provide a linear response under a specific loading condition and provide a different response for other loading directions. With these specifications in mind, our team created a soft elastomeric sensor designed to provide force feedback during cardiac catheter ablation surgery. Analytical and computational methods were explored to define a relationship between resistance and applied force for a semicircular, liquid metal filled channel in the soft elastomeric sensor. Pouillet’s Law is utilized to calculate the resistance based on the change in cross-sectional area resulting from various applied pressures. FEA simulations were created to simulate the deformation of the sensor under various loads. To confirm the validity of these simulations, the elastomer was modeled as a neo-Hookean material and the liquid metal was modeled as an incompressible fluid with negligible shear modulus under uniaxial compression. Results show a linearly proportional relationship between the resistance of the sensor and the application of a uniaxial force. Altering the direction of applied force results in a quadratic relationship between total resistance and the magnitude of force.


2020 ◽  
Vol 30 (46) ◽  
pp. 2004417
Author(s):  
Antonio López‐Díaz ◽  
Ana Martín‐Pacheco ◽  
Antonio M. Rodríguez ◽  
M. Antonia Herrero ◽  
Andrés S. Vázquez ◽  
...  

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