MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Doctoral Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Doctoral Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Function Follows Form: An Exploration of Robotic Embodiment through Geometry

Author(s)
Chin, Lillian Tiffany
Thumbnail
DownloadThesis PDF (29.13Mb)
Advisor
Rus, Daniela
Terms of use
In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/
Metadata
Show full item record
Abstract
Current robot designers often treat a robot’s body as merely a vessel to transport the brain, limiting the potential scope of “embodied intelligence” that is unique to robotics. This cognitivist approach to robot design is in-line with critiques from disability studies, which argues that assuming a single normative body ignores the diversity of human body-environment interactions, unfairly limiting human potential. This thesis aims to use framings from disability studies to better inform robotic design practice. By examining interactions between a body and its environment — whether a human body or a robotic one — we gain a better understanding of the necessary materials and tools needed to make that interaction a successful one. I am particularly interested in using geometry as a design tool for robot bodies, especially given the potential of mechanical metamaterials in robotic design. After first discussing bodies, materials and geometry’s impact on form in both disability studies and robotics, I demonstrate the power of this approach through two main case studies. First, I introduce AuxBots, a set of modular robots that use a motorized auxetic shell to control their volumetric expansion. Since the AuxBot’s expansion was achieved purely through geometry, I had significant control over the design space. I created AuxBots optimized for speed and expansion ratio (390% volume expansion in 0.2 seconds) or for force output (135 N max, or 76x strength-weight ratio, one of the highest ratios of any modular robot). I was able to explicitly make trade-offs between stiffness, speed, and force as a direct consequence of how the geometric parameters affect the overall system behavior. My second example is the technique of fluidic innervation, a sensorization strategy that patterns empty air channels within the struts of a 3D printed metamaterial. When the metamaterial deforms, these air channels will have their volume changed, which, by the Ideal Gas Law, can then be measured using an off-the-shelf pressure sensor. This combines perception directly with the underlying geometry of the metamaterial itself, since the channels follow the same structural elements that form the overall metamaterial. When complex metamaterials (ex. handed shearing auxetics) are sensorized, fully proprioceptive soft robotic systems can be created as structure, actuation and sensing are embedded into one single geometry. These examples demonstrate not only the power of using geometry as a design tool, but also the potential for combining social science approaches for robotic development.
Date issued
2023-06
URI
https://hdl.handle.net/1721.1/151699
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology

Collections
  • Doctoral Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.