Morphogenetically Assisted Design Variation (MADV)
Funded by DARPA DSO under the Maximum
Mobility and Manipulation (M3) program
Contact Email: firstname.lastname@example.org
Troops in theater are often the first to discover an emerging
need, and often have creative ideas of how to address it.
The ongoing revolution in
fast prototyping and lightweight manufacturing technology will soon
remove the physical impediments to creating new systems in the field:
what is needed are design tools that will allow non-experts, e.g.,
soldiers, to create variations on existing designs that will better
suit operational needs.
Design experts not only know which parts
must be changed to accomplish a new objective, but more importantly
anticipate the impact this change will have on other components.
These are critical skills that non-expert users lack, and they are
perfect tasks for a smart design tool. The tool should adapt other
components to support and compensate for these changes, and
should support rapid fabrication of the final design.
Consider a soldier in the field with a small surveillance robot that
can climb over obstacles up to a certain height, e.g., small rocks. The
soldier's next mission
is in an area that contains larger obstacles that the robot cannot
handle, such as tall stairs. In order to accomplish the mission, the
soldier needs a way to make a variation of the robot that fits the new
requirements. However, he is not a robotics expert.
We aim to fill this gap with Morphogenetically Assisted Design
Variation (MADV). A military base equipped with MADV tools running on a
computer and connected manufacturing capabilities, such as a 3D
printer, would allow the soldier to modify the design and fabricate
the necessary parts to create the robot he needs. This design can
then be shared with other soldiers and evaluated for addition to
In this project, we focus on robotic design, where systems are
typically complex and highly integrated, yet relatively small and
inexpensive. In particular, we focus on an example robot similar to
the iRobot LANdroid, but simpler and less expensive, which we are
“miniDroid.” Increasing the speed of such a robot might require
changing the size of the motor. This in turn could affect the battery
size, the control circuit board, the size of the chassis needed to
accommodate all the components, etc. Even small design changes have a
ripple effect through many other components of the robot. Finally,
since robotics is a particularly challenging domain, progress
in this domain may be applicable to other domains.
MADV pre-alpha release, November
MADV pre-alpha release 3, February
End of year 1 video demonstrating 5x
variation for step climbing, wmv format, m4v format
and driving simulations for minidroid (m4v, mov, mp4)
Variant miniDroids: able to climb
much larger step (m4v, mov,
mp4), high undercarriage clearance (m4v,
Early stages of
body-plan development for a miniDroid robot, including distortion
Publications & Talks
- A Morphogenetically Assisted
Design Variation Tool,
Aaron Adler, Fusun Yaman, Jacob Beal, Jeffrey Cleveland, Hala Mostafa,
and Annan Mozeika. Proceedings of the Twenty-Seventh AAAI Conference on
Artificial Intelligence. Bellevue, Washington, July 2013, pp. 9-15. [Talk]
- Mixed Geometric-Topological
Representation for Electromechanical Design,
Jacob Beal, Aaron Adler, and Hala Mostafa. Proceeding of the Fifteenth
Annual Conference Companion on Genetic and Evolutionary Computation
Conference Companion (GECCO 13 Companion). Amsterdam, The Netherlands,
July 2013, pp 105-106.
Self-Organization Approaches to Adaptive Design, Jacob Beal, 2012
Conference on Through-Life Engineering Services, November 2012.
Dimensionless Graceful Degradation Metric for Quantifying Resilience,
Jacob Beal, Workshop on Evaluation of Self-Adaptive and Self-Organizing
Systems, IEEE SASO, September, 2012.
Manifold Operator Representation for Adaptive Design,
Jacob Beal, Hala Mostafa, Annan Mozeika, Benjamin Axelrod, Aaron Adler,
Gretchen Markiewicz, Kyle Usbeck, Proceedings of the Fourteenth
International Conference on Genetic and Evolutionary Computation
Conference (GECCO '12), pp. 529-536, July 2012.
- On the
Evaluation of Space-Time Functions, Jacob Beal, Kyle Usbeck, and
Brett Benyo, The Computer Journal, online July 2012, final 56 (12) pp.
1500-1517, November, 2013.
- An Agent
Framework for Agent Societies, Kyle Usbeck, Jacob Beal, Actors and
Agents Reloaded (AGERE) at SPLASH 2011, October 2011.
Morphogenetic Models to Develop Spatial Structures, Jacob Beal,
Jessica Lowell, Annan Mozeika, Kyle Usbeck. Spatial Computing Workshop
(SCW) at IEEE SASO 2011, October 2011.[Talk]
- On the
Evaluation of Space-Time Functions, Jacob Beal, Kyle Usbeck,
Spatial Computing Workshop (SCW) at IEEE SASO 2011, October 2011.
- Morphogenetically Assisted
Aaron Adler, Fusun Yaman, Jeffrey Cleveland,
and Jacob Beal, extended abstract for 2nd International Conference on
Morphological Computation. September 2011, Venice, Italy. [Poster]
- Morphogenesis as a
Reference Architecture for Engineered Systems,
Jacob Beal, Annan Mozeika, Jessica Lowell, and Kyle Usbeck, extended
abstract for 3rd Morphogenetic Engineering Workshop (MEW) at ECAL 2011,
Blueprints: An Approach to Modularity in Grown Systems,
Jacob Beal, online publication in Swarm Intelligence Journal, June
- Functional Blueprints:
An Approach to Modularity in Grown Systems, Jacob Beal, 7th
Conference on Swarm Intelligence (ANTS 2010), September 2010.