The concept of active subtraction (see the literature below) provides a promising approach: modules can detach or remove themselves from an existing configuration to enable self-reconfiguration, complementing traditional assembly strategies. This approach has been shown to be possible in two-dimensional modular robotic systems, demonstrating that complex reconfigurations can emerge from simple local rules.

In this thesis, you explore extensions and new directions for active subtraction in modular robotics. Possible directions include:

• Extending active subtraction to three-dimensional reconfiguration, investigating how modules can safely detach and reposition in a volumetric space.
• Analyzing optimization of reconfiguration sequences, minimizing the number of moves, time, or energy consumed by the system.
• Studying hybrid strategies that combine active subtraction with active addition (attaching modules) for more versatile reconfiguration.
• Investigating fault tolerance, for example when some modules fail to detach or reattach correctly.
• Evaluation of these methods in physics-based simulations.

This topic lies at the intersection of modular robotics, self-reconfiguration, and distributed algorithms, and is suitable for students interested in algorithmic design and analysis, simulation, and emergent behavior of modular robots. If you are interested in this topic, please send an email to both Prof. Groß and Julian Rau including a brief motivation letter, your CV, and your current transcript of records.

Core data

Publications

• Matthew D. Hall, Anıl Özdemir and Roderich Groß: Self-Reconfiguration in Two-Dimensions via Active Subtraction with Modular Robots.
• Matthew D. Hall: Active Subtraction: A Viable Method of Self-Reconfiguration for Modular Robotic Systems.