Patterned Assembly of Multibiological Robots With Global Input

Engineered assembloids fabricated from tissue spheroids hold immense promise for developmental biology, disease modeling, and regenerative medicine. However, fabricating heterogeneous assembloids with precise spatial patterning remains a critical bottleneck, often reliant on manual pipetting that lacks scalability and reproducibility. While magnetic microrobotics, which transforms spheroids into controllable robots, offers a non-invasive alternative, it faces a fundamental challenge: the global input of magnetic actuation. A single command moves all robots simultaneously, leading to coupled motion and frequent assembly failures. Here, we present a collaborative control framework that overcomes this limitation by leveraging local constraints and a novel motion decoupling strategy. We reformulate the high-dimensional, coupled multi-robot planning problem into a low-dimensional aggregate space, effectively transforming the assembly task into a dynamic sequential decision problem. This framework, coupled with a graph-based dynamic path optimization algorithm, enables deterministic, collision-free assembly. Experimental validation demonstrates a 78.57% higher success rate and a 33.20% higher assembly efficiency compared to conventional strategies. This work establishes a foundational engineering principle for assembloid fabrication, transitioning the process from a qualitative experiments to a controllable and programmable engineering discipline, thereby unlocking the potential for deterministic construction of complex biological structures.