Selective Self-Assembly using Re-Programmable Magnetic Pixels
Martin Nisser, Yashaswini Makaram, Faraz Faruqi, Ryo Suzuki, and Stefanie Mueller

TL;DR
This paper presents a magnetic encoding method for physical modules that enables highly selective and re-programmable self-assembly into desired shapes, verified through experiments with cubic modules in water.
Contribution
It introduces a Hadamard matrix-based magnetic encoding technique for re-programmable, selective self-assembly of modules without geometric guides.
Findings
Successful self-assembly of 8 cubes in water
Modules can be re-programmed with a CNC magnetic plotter
Encoding guarantees attraction to intended mates
Abstract
This paper introduces a method to generate highly selective encodings that can be magnetically "programmed" onto physical modules to enable them to self-assemble in chosen configurations. We generate these encodings based on Hadamard matrices, and show how to design the faces of modules to be maximally attractive to their intended mate, while remaining maximally agnostic to other faces. We derive guarantees on these bounds, and verify their attraction and agnosticism experimentally. Using cubic modules whose faces have been covered in soft magnetic material, we show how inexpensive, passive modules with planar faces can be used to selectively self-assemble into target shapes without geometric guides. We show that these modules can be easily re-programmed for new target shapes using a CNC-based magnetic plotter, and demonstrate self-assembly of 8 cubes in a water tank.
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Taxonomy
TopicsModular Robots and Swarm Intelligence · Advanced Materials and Mechanics · Interactive and Immersive Displays
