Defense Date


Document Type


Degree Name

Master of Science


Electrical & Computer Engineering

First Advisor

Patrick Martin


This thesis presents a real-time robotic motion control system for human-robot teams. The framework utilizes artificial potential fields (APFs) to guide robotic agents towards a “goal” agent while navigating around “obstacle” agents; these goals and obstacles are also dynamic agents with their own set of tasks. This system is also developed for a live-programming environment, where a controlling agent updates the tasks of all agents within the system at any time during the system’s runtime. This motion controller was created and tested for a human-robot choreographic team. After the controller was fully integrated on a Trossen Robotic LoCobot Wx200 robotic base, a live, interactive dance titled Together::Apart was performed utilizing the controller and supporting systems, and audience members were asked to evaluate the human-robot team. In addition, because APFs produce straight-line agent- to-goal trajectories, a new, mixed artificial field (MAF) motion controller was developed. By introducing an additional static field, the MAF controller is able to modify the robot’s path into non-linear contours. After simulating the MAF controller in Python, the model was recorded and evaluated by a survey, using several factors from the Godspeed questionnaire. The survey results were analyzed and discussed in order to determine directions for future work.


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Available for download on Thursday, August 01, 2024