CSCI 7000: Robotic Materials

Photo May 14, 11 37 41 AM
Prototype of a soft autonomous material that can roll using distributed control
Honeycomb testbed with 48 nodes
CSCI 7000: Robotic Materials is a graduate project class that will lay the foundations of a new class of metamaterials that embed sensing, actuation, computation and communication. Examples of robotic materials are rods and sheets that can change their stiffness and shape, sense pressure, vibrations or temperature at high density, or are able to self-diagnose and self-repair.Technically, Robotic Materials are composite materials that tightly embed sensors, computers, actuators as well as power and communication. Mathematically, Robotic Materials are networked hybrid systems consisting of continuous material dynamics and discrete algorithms, thereby spanning a variety of disciplines ranging from robotics, electrical, aerospace and materials engineering to computer science.The class consists of a lecture and lab part. While the lecture will review a series of selected concepts ranging from controls and hybrid automata to spatial and amorphous computing, the lab part will provide practical knowledge on how to manufacture robotic materials using standard composite materials manufacturing techniques and a miniature embedded computing platform developed in our lab.In lieu of homeworks and a final exam, the students will complete the following deliverables: a tutorial on a selected topic that will be part of a textbook to be used in future iterations of this class (individual project), and implementation of a robotic material in wood, concrete, fiber enforced polymers, rubber, metal or cloth using the tools provided during lab (group project).

Prerequisites: strong background in at least one of the following: robotics, composites, control theory, networking, embedded systems, or algorithms.

Meetings: TTH, 5pm-6.15pm ECCS 1B21

Grading: 40% tutorial, 40% final project, 20% class contribution. Due to the collaborative nature of the class the following rules will be strictly enforced: (1) Attendance is required. (2) Missing deadlines will result into 0.5 grade pt/week grade reduction for this component of class. Reasonable excuses are health, professional travel, and religious observance.

Course fee: $75 for consumables used during class



Lecture Lab Deliverable
Week 1 Class introduction What are Robotic Materials?
Week 2 Case Study: High-bandwidth signal processing: texture recognition in artificial skins (Dana Hughes) Glass fiber composites with embedded sensing, actuation, and comutation Topic selection: Tutorial
Week 3 Case study: Shape-change via programmable stiffness
(Andy McEvoy)
 Laser cutting workshop
Week 4 Project Selection Project Selection Topic selection: Final project
Week 5 Case study: Distributed Gesture Recognition in an Amorphous Facade(Nick Farrow)  3D Printing workshop
Week 6 Graph-theoretical foundations of robotic materials
(Michael Barnabei)
Week 7 Local algorithms for robotic materials(Abishek Narula) PDR Preliminary design review: What will your material do and how will it do it?
Week 8 Distributed vector graphics on robotic materials(Kansuke Ikehara) Project Tutorials due
Week 9 Soft robotic materials(Muhammed Hamza) Project
Week 10 Tutorials CDR Critical design review: Demonstrate the component that is critical for the function of your robotic material
Week 11 Tutorials  Project
Week 12 Tutorials Project
Week 13 Tutorials Project
Week 14 Fallbreak
Week 15 Project
Week 16 Final presentations

Case Studies

  1. D. Hughes, N. Correll (2014): A Soft, Amorphous Skin that can Sense and Localize Texture . IEEE International Conference on Robotics and Automation (ICRA), Hong Kong.
  2. M. A. McEvoy, N. Correll (2014): Shape Change Through Programmable Stiffness. International Symposium on Experimental Robotics (ISER), Springer Verlag, Marrakech, Morocco.
  3. N. Farrow, N. Sivagnanadasan, N. Correll (2014): Gesture Based Distributed User Interaction System for a Reconfigurable Self-Organizing Smart Wall. In: Proceedings of the 8th International Conference on Tangible, Embedded and Embodied Interaction (TEI), ACM.


  1. Michael Barnabei: Duckham, M. (2013). Formal Foundations of Decentralized Spatial Computing: Foundations of Geosensor Networks. Springer.
  2. Abhishek Narula: Suomela, J. (2013). Survey of local algorithmsACM Computing Surveys (CSUR)45(2), 24. Tutorial: Local algorithms for Robotic Materials.
  3. Kansuke Ikehara: Butera, W. (2007, July). Text display and graphics control on a paintable computer. In Self-Adaptive and Self-Organizing Systems, 2007. SASO’07. First International Conference on (pp. 45-54). IEEE. Tutorial: Distributed algorithms for displaying graphics and text.  
  4. Muhammed Hamza: Majidi, C. (2013). Soft Robotics – A Perspective. Soft Robotics Journal 1(1):5-11.


  • Muhammed Hamza and Nick Farrow: a variable stiffness thermoplastic that keeps its shape.
  • Michael Barnabei and Dana Hughes: a touchless touchsensing skin.
  • Kansuke Ikehara and John Klingner: the yellow brick road.
  • Abishek Narula and Ankit Saxena: movement through sound.



  • What kind of platform will we be using? We have developed a small microcontroller board based on the Atmel Xmega 128A3, which is equipped with an accelerometer, a thermistor, a microphone, an LED and various hook-ups for other digital/analog in- and output. Each board can be networked with its 4-neighborhood using a dedicated serial port. We have already developed a number of tools and operating system components for this platform using AVR studio (C/C++).
  • What is the course fee being used for? We will provide materials for you to make your own fibre glass/carbon composite. We will also provide each group with a limited amount (10-20) of the boards we have developed.
  • Will the course project be sufficient for a paper? Yes, we actually hope that we can publish a paper together in the Journal of Composite Materials, Smart Materials and Structures or similar. Getting your work into paper form will likely require additional work after the end of the class, however.
  • Will we get credit for the textbook you are writing? We plan to release the textbook under a creative commons license and make it available via github and Each chapter will be co-authored by a growing number of authors (you) and be released as edited volume.
  • What are the time requirements for this class? In addition to regular meetings, we will try to identify both your tutorial and class project early on in class, resulting in a workload of a minimum of 6-10h per week.
  • Isn’t that way too much stuff? Have a look at GEEN1400: Materials that think and the awesome final projects the freshmen came up with.
  • I’m an undergraduate student, can I still take the class? Yes, in particular if you have a strong background in at least one of the above topics (prerequisites) or you have taken “Materials that think”. You will be graded differently than the graduate students.
  • I’m a graduate student outside of CS and not comfortable with programming, can I still take the class? Yes, if you have a strong background in at least one of the prerequisites that you can contribute.


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