Master Thesis, Bartlett School of Architecture, University College of London
Supervisor: Valentina Soana
Year: 2020
Programming Languages Used: C#, Grasshopper
Software Used: Rhino, Unity
This research addresses the structural requirements of building dynamic structures of modular robots and proposes a structurally-driven control system for a self-reconfigurable robotic system based on the structural analysis and performance of not only the final target configuration of a robotic assembly but also of the intermediate transitional configurations achieved during self-reconfiguration. To formulate a structurally feasible target shape, a topology optimization is used to evolve the target shape based specific boundary and loading conditions and maximize structural stiffness. Thereafter, the control strategy drives the modules’ decision-making process using three fitness criteria for action selection: modules’ convergence towards the given target configuration, stability of the overall assembly, and the structural performance of the assembly. The work of this research is documented here.