Semester

Fall

Date of Graduation

2019

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Mechanical and Aerospace Engineering

Committee Chair

Yu Gu

Committee Member

Yu Gu

Committee Member

Jason Gross

Committee Member

Guilherme Pereira

Abstract

This thesis presents Virtual Morphology (VM), a method that explores a different perspective on the design of robot autonomy using inspiration from morphological computing and programmed computation. Morphological computation offers physical solutions that solve complex tasks, like robotic grasping of unknown objects, with relative ease. Unfortunately, these physical solutions are difficult to adjust post-development, and are usually designed to complete only one or a few specific tasks. Programmed computational approaches are more flexible because they can be implemented and adjusted through software, but unfortunately, these approaches can become rather complex as tasks become more difficult. This thesis explores the potential of mixing these methods by implementing morphologic computation, virtually, to couple it with programmed methods; It is implemented through an existing medium of robotics work defined here as artificial physics (AP). The blending occurs by allowing physics simulation to control a physical robot from the interactions produced in the virtual space. The virtual space is projected onto the physical environment to provide robot designers an intuitive understanding of how the interactions dictate the behavior of the physical robot. By utilizing different virtual morphologies, the behavior of the robot can be altered, intuitively. Several case studies demonstrate the capability of VM to generate autonomous behavior. The experiments show that VM can successfully fuse several benefits of morphological computing, such as productive use of passive environmental interactions, with several benefits of programmed autonomy, such as the implementation of high-level goals and quickly changing parameters to adapt for different situations.

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