Exploration of icy moons in the search for extra-terrestrial life is becoming a major focus in the NASA community. As such, the Exobiology Extant Life Surveyor (EELS) robot has been proposed to survey Saturn's Moon, Enceladus. EELS is a snake-like robot that will use helically grousered wheels to propel itself forward through the complex terrains of Enceladus. This moon's surface is composed of a mixture of snow and ice. Mobility research in these types of terrains is still under-explored, but must be done for the EELS robot to function. As such, this thesis will focus on the methodologies required to effectively simulate wheel interaction with cohesive media from a computational perspective. Three simulation tools will be briefly discussed: COMSOL Multiphysics, EDEM-ADAMS, and projectChrono. Next, the contact models used in projectChrono will be discussed and the methodology used to implement a custom Johnson Kendall Roberts (JKR) collision model will be explained. Finally, initial results from a cone penetrometer test in projectChrono will be shown. Qualitatively, the final simulations look correct, and further work is being done to quantitatively validate them as well as simulate more complex screw geometries.

Medical technology, while improving greatly with time, often requires a sacrifice in the form of invasiveness in order to reach target areas within the body, such as the brain, liver, or heart. This project aims to utilize a magnetic, flexible needle design to reach these target areas for surgery and drug administration with minimal invasiveness. The metallic needle tip is guided by an external system consisting of a UR16e robotic arm with a magnetic end effector. As a longer running project, the primary focuses of this research are to develop the system by which the robotic arm guides the needle, investigate and implement fiber Bragg grating sensors as a means of real time path imaging and feedback, and conduct preliminary tests to validate that the needle is accurately controlled by the robotic arm. Testing with different mediums such as gel or phantom tissue, and eventually animal experiments will follow in a future publication due to time constraints.

This project compared two optimization-based formulations for solving multi-robot task allocation problems with tether constraints. The first approach, or the ”Iterative Method,” used the common multiple traveling salesman (mTSP) formulation and implemented an algorithm over the formulation to filter out solutions that failed to satisfy the tether constraint. The second approach, named the ”Timing Formulation,” involved constructing a new formulation specifically designed account for robot timings, including the tether constraint in the formulation itself. The approaches were tested against each other in 10-city simulations and the results were compared. The Iterative Method could provide answers in 1- and 2-norm variations quickly, but its mTSP model formulation broke down and became infeasible at low city numbers. The 1-norm Timing Formulation quickly and reliably produced solutions but faced high computation times in its 2-norm manifestation. Ultimately, while the Timing Formulation is a more optimal method for solving tether-constrained task allocation problems, its reliance on the 1-norm for low computation times causes it to sacrifice some realism.

This thesis presents the design and simulation of an energy efficient controller for a system of three drones transporting a payload in a net. The object ensnared in the net is represented as a mass connected by massless stiff springs to each drone. Both a pole-placement approach and an optimal control approach are used to design a trajectory controller for the system. Results are simulated for a single drone and the three drone system both without and with payload.

The objective goal of this research is to maximize the speed of the end effector of a three link R-R-R mechanical system with constrained torque input control. The project utilizes MATLAB optimization tools to determine the optimal throwing motion of a simulated mechanical system, while mirroring the physical parameters and constraints of a human arm wherever possible. The analysis of this final result determines if the kinetic chain effect is present in the theoretically optimized solution. This is done by comparing it with an intuitively optimized system based on throwing motion derived from the forehand throw in Ultimate frisbee.