Author ORCID Identifier

https://orcid.org/0000-0002-3193-520X

Semester

Spring

Date of Graduation

2025

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Mechanical and Aerospace Engineering

Committee Chair

Nicholas Szorcinski

Committee Co-Chair

Valeriya Gritsenko

Committee Member

Valeriya Gritsenko

Committee Member

Stephen Cain

Committee Member

Yu Gu

Committee Member

Sergiy Yakovenko

Abstract

For decades, the field of biologically inspired robotics has leveraged insights from animal locomotion to improve the walking ability of legged robots. Recently, “biomimetic” robots have been developed to model how specific animals walk. By prioritizing biological accuracy to the target organism rather than the application of general principles from biology, these robots can be used to develop detailed biological hypotheses for animal experiments, ultimately improving our understanding of the biological control of legs while improving technical solutions. Much of this work involves biologically inspired walking controllers informed by the morphology and dynamics of the insect nervous system, which necessitate a robot with highly animal-like structure to prevent a brain-body mismatch. However, methods for codifying suitable fidelity in biomimetic robots currently vary, with limited generalizable methods for robot design. In this work, I outline a general framework for developing biomimetic robots that ensures kinematic and dynamic similarity between the robot and target animal. I then use this framework to develop and validate the robot Drosophibot II, a meso-scale robotic model of an adult fruit fly, Drosophila melanogaster. The resulting robot is novel for its close attention to the kinematics and dynamics of Drosophila, an increasingly important model of legged locomotion. Each leg’s proportions and degrees of freedom are modeled after Drosophila 3D pose estimation data. The predominant actuators for the robot are characterized to determine their inertial, elastic, and viscous properties and subsequently dynamically scale the robot's motions. I then use a developed program to automatically solve the inverse kinematics and inverse dynamics necessary for walking for the robot's structure and that of a to-scale model of the fly. By comparing the output of these models, I demonstrate that the robot and fly are kinematically and dynamically similar. The robot's electromechanical design is presented, then validated by having the robot’s walk forward, backward, and up an incline via open-loop straight line stepping with biologically inspired foot trajectories. Strain data from locations throughout the robot's legs is also recorded during these tests as an analog for mechanosensory feedback in a freely walking animal. Through these experiments, Drosophibot II demonstrates its utility for neuromechanical investigations by providing plausible neural data currently unobtainable in the animal.

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