Printing of Recyclable Robots

Recent advances in 3D printing are revolutionizing manufacturing, enabling the fabrication of structures with unprecedented complexity and functionality. Yet biological systems are able to fabricate systems with far greater complexity using a process that involves assembling and folding a linear string. Here, we demonstrate a 1D printing system that uses an approach inspired by the ribosome to fabricate a variety of specialized robotic automata from a single string of source material. This proof-ofconcept system involves both a novel manufacturing platform that configures the source material using folding and a computational optimization tool that allows designs to be produced from the specification of high-level goals. We show that our 1D printing system is able to produce three distinct robots from the same source material, each of which is capable of accomplishing a specialized locomotion task. Moreover, we demonstrate the ability of the printer to use recycled material to produce new designs, enabling an autonomous manufacturing ecosystem capable of repurposing previous iterations to accomplish new tasks.

[1]  Zhe Li,et al.  Polymer filament–based in situ microrobot fabrication using magnetic guidance , 2016 .

[2]  Fionnuala Connolly,et al.  Automatic design of fiber-reinforced soft actuators for trajectory matching , 2016, Proceedings of the National Academy of Sciences.

[3]  Robert J. Wood,et al.  An integrated design and fabrication strategy for entirely soft, autonomous robots , 2016, Nature.

[4]  Ronald S. Fearing,et al.  Robotic folding of 2D and 3D structures from a ribbon , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[5]  Daniela Rus,et al.  Printable hydraulics: A method for fabricating robots by 3D co-printing solids and liquids , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[6]  Martin L. Dunn,et al.  Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers , 2015, Scientific Reports.

[7]  Yu Cheng,et al.  Interactive robogami: data-driven design for 3D print and fold robots with ground locomotion , 2015, SIGGRAPH Studio.

[8]  Chen Yang,et al.  3D-printed microelectronics for integrated circuitry and passive wireless sensors , 2015 .

[9]  Jonas Neubert,et al.  Soldercubes: a self-soldering self-reconfiguring modular robot system , 2016, Auton. Robots.

[10]  F. Iida,et al.  Morphological Evolution of Physical Robots through Model-Free Phenotype Development , 2015, PloS one.

[11]  A. E. Eiben,et al.  From evolutionary computation to the evolution of things , 2015, Nature.

[12]  Daniela Rus,et al.  An untethered miniature origami robot that self-folds, walks, swims, and degrades , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[13]  Daniela Rus,et al.  Integrated Codesign of Printable Robots , 2015 .

[14]  Antoine Cully,et al.  Robots that can adapt like animals , 2014, Nature.

[15]  Daniela Rus,et al.  Foldable Joints for Foldable Robots , 2015, ISER.

[16]  Ramesh Raskar,et al.  Active Printed Materials for Complex Self-Evolving Deformations , 2014, Scientific Reports.

[17]  Mark Yim,et al.  Design, principles, and testing of a latching modular robot connector , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Daniela Rus,et al.  Cogeneration of mechanical, electrical, and software designs for printable robots from structural specifications , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[19]  Hod Lipson,et al.  Bitblox: Printable digital materials for electromechanical machines , 2014, Int. J. Robotics Res..

[20]  Samuel M. Felton,et al.  A method for building self-folding machines , 2014, Science.

[21]  E. Sivertsson,et al.  Protein folding: When ribosomes pick the structure. , 2014, Nature chemistry.

[22]  Joshua Evan Auerbach,et al.  Environmental Influence on the Evolution of Morphological Complexity in Machines , 2014, PLoS Comput. Biol..

[23]  Wojciech Matusik,et al.  Computational design of mechanical characters , 2013, ACM Trans. Graph..

[24]  Sebastian Risi,et al.  Ribosomal robots: evolved designs inspired by protein folding , 2013, GECCO '13.

[25]  Neil Gershenfeld,et al.  The Milli-Motein: A self-folding chain of programmable matter with a one centimeter module pitch , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[26]  J. Lewis,et al.  Reactive silver inks for patterning high-conductivity features at mild temperatures. , 2012, Journal of the American Chemical Society.

[27]  J. Clune,et al.  Evolving 3D objects with a generative encoding inspired by developmental biology , 2011, SEVO.

[28]  Kenneth O. Stanley,et al.  Picbreeder: A Case Study in Collaborative Evolutionary Exploration of Design Space , 2011, Evolutionary Computation.

[29]  Erik D. Demaine,et al.  Programmable Assembly With Universally Foldable Strings (Moteins) , 2011, IEEE Transactions on Robotics.

[30]  Kenneth O. Stanley,et al.  Abandoning Objectives: Evolution Through the Search for Novelty Alone , 2011, Evolutionary Computation.

[31]  Kenneth O. Stanley,et al.  Autonomous Evolution of Topographic Regularities in Artificial Neural Networks , 2010, Neural Computation.

[32]  Jonas Neubert,et al.  A robotic module for stochastic fluidic assembly of 3D self-reconfiguring structures , 2010, 2010 IEEE International Conference on Robotics and Automation.

[33]  Daniela Rus,et al.  Robot pebbles: One centimeter modules for programmable matter through self-disassembly , 2010, 2010 IEEE International Conference on Robotics and Automation.

[34]  Ricardo Franco Mendoza Garcia,et al.  Mechanical design of odin, an extendable heterogeneous deformable modular robot , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[35]  Temple F. Smith,et al.  The origin and evolution of the ribosome , 2008, Biology Direct.

[36]  Kenneth O. Stanley,et al.  Compositional Pattern Producing Networks : A Novel Abstraction of Development , 2007 .

[37]  Risto Miikkulainen,et al.  Evolving Neural Networks through Augmenting Topologies , 2002, Evolutionary Computation.

[38]  S. Lloyd.  Computational capacity of the universe. , 2001, Physical review letters.

[39]  Jordan B. Pollack,et al.  Evolution of generative design systems for modular physical robots , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[40]  K. Ohji,et al.  Cumulative Damage and Effect of Mean Strain in Low-Cycle Fatigue of a 2024-T351 Aluminum Alloy , 1966 .

[41]  W. Oechel,et al.  Automatic design and manufacture of robotic lifeforms , 2022 .