A 3D-printed, functionally graded soft robot powered by combustion

By Nicholas W. Bartlett, Michael Thomas Tolley, Johannes T. B. Overvelde, J. Weaver, Bobak Mosadegh, Katia Bertoldi, George M. Whitesides, Robert J. Wood. Science, 2015

986 citations recorded by the source corpus.

Making jack jump efficiently In the future, soft-bodied robots may be able to squeeze into tight spaces or work in environments where they could be crushed. However, it is hard to ensure efficient power transmission in a soft-bodied device. One promising solution is to use explosions to drive the robot, using efficient weight-to-power energy sources. Using three-dimensional printing to fuse together multiple materials, Bartlett et al. built a combustion-powered robot. The robot has a rigid core that transitions to a soft exterior. They produced an efficient jumping robot in which the gradations in the hardness of the body materials also improved robustness. Science, this issue p. 161 Gradual interfacing of soft and rigid components creates a more robust, untethered, jumping soft robot. Roboticists have begun to design biologically inspired robots with soft or partially soft bodies, which have the potential to be more robust and adaptable, and safer for human interaction, than traditional rigid robots. However, key challenges in the design and manufacture of soft robots include the complex fabrication processes and the interfacing of soft and rigid components. We used multimaterial three-dimensional (3D) printing to manufacture a combustion-powered robot whose body transitions from a rigid core to a soft exterior. This stiffness gradient, spanning three orders of magnitude in modulus, enables reliable interfacing between rigid driving components (controller, battery, etc.) and the primarily soft body, and also enhances performance. Powered by the combustion of butane and oxygen, this robot is able to perform untethered jumping.

Subfields: Biomedical Engineering, Condensed Matter Physics, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/c3a6609f3f6737dbb71d08dc695edea664a3e841

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

  1. Matteo Cianchetti
  2. Barbara Mazzolai
  3. J. Lewis
  4. Michael Thomas Tolley
  5. Andre Rosendo
  6. Chiara Daraio
  7. Bernard Bayle
  8. Utku Çulha

In Condensed Matter Physics

  1. Matteo Cianchetti
  2. Barbara Mazzolai
  3. J. Lewis
  4. Michael Thomas Tolley
  5. Andre Rosendo
  6. Chiara Daraio
  7. Utku Çulha
  8. Fumiya Iida

In Mechanical Engineering

  1. Matteo Cianchetti
  2. Barbara Mazzolai
  3. J. Lewis
  4. Michael Thomas Tolley
  5. Andre Rosendo
  6. Chiara Daraio
  7. Utku Çulha
  8. Fumiya Iida

Citations in the corpus