Author ORCID Identifier
Semester
Summer
Date of Graduation
2026
Document Type
Dissertation
Degree Type
PhD
College
Statler College of Engineering and Mineral Resources
Department
Mechanical and Aerospace Engineering
Committee Chair
Yu Gu
Committee Member
Nicholas Szorcinski
Committee Member
Sergiy Yakovenko
Committee Member
Adam Halasz
Committee Member
Anand Mishra
Abstract
Designing robots traditionally relies on centralized, top-down methods that constrain adaptability and resiliency, producing systems optimized for specific tasks. However, such systems often fail in complex environments, such as extraterrestrial, disaster, or natural settings, where designers cannot foresee every scenario a robot may encounter. Achieving autonomy in these contexts requires robots that are resilient and capable of adapting to the unknown. Multicellular organisms exhibit this adaptability through self-organization, where complex structures and behaviors emerge from local interactions among their cells. Such organisms can be viewed simultaneously as a single entity and a swarm of cooperating cells, i.e., a Swarm-of-One.
This research extends the Swarm-of-One paradigm to robotics, in which the robot’s form and function are not predetermined but emerge from the decentralized interactions among its components and the environment. The results of this work have demonstrated the spontaneous self-organization of robotic cells into macroscopic morphologies with differentiated mechanical properties, supporting their coherent behavior under changing environmental constraints. In addition, a general design methodology for self-organizing multi-cellular robots was formalized, where the robot emerges from a cooperative process among the designer, the environment, and the robot itself. Moreover, self-organization is extended to conventional robots as a tool for solving task allocation and planning problems for high-degree-of-freedom systems, which are computationally difficult to solve centrally. This approach reframes robot design from a purely offline process to one that integrates online adaptation, enabling robots to change their bodies and behaviors to the environment. In doing so, it establishes a pathway toward scalable, high-degree-of-freedom systems that operate robustly in unstructured, unknown, and changing environments.
Recommended Citation
Smith, Trevor Riley, "Swarm of One: Self-Organization in Multicellular Robots" (2026). Graduate Theses, Dissertations, and Problem Reports (ETD). 13400.
https://researchrepository.wvu.edu/etd/13400
Included in
Computational Biology Commons, Computational Neuroscience Commons, Developmental Biology Commons, Dynamics and Dynamical Systems Commons, Electro-Mechanical Systems Commons, Robotics Commons