Design and Control of Modular Magnetic Millirobots for Multimodal Locomotion and Shape Reconfiguration
Erik Garcia Oyono, Jialin Lin, Dandan Zhang
AI summary
Problem
Existing modular magnetic microrobots rely on boundary collisions for reconfiguration, require bulky high-field actuation systems, and lack robust independent single-module control, limiting their safety and applicability in biomedical settings.
Approach
The team developed three specialized cube-shaped modules controlled by programmable 2D uniform and gradient magnetic fields, enabling independent locomotion and collision-free reconfiguration without relying on physical boundaries.
Key results
- Deterministic flip-and-walk locomotion under low magnetic fields (<13 mT)
- Collision-free self-assembly and chain-to-gripper reconfiguration (90% success)
- Closed-loop maze navigation using real-time vision feedback and A* path planning
- Cavity geometry tuning to prioritize flexible reconfiguration or stable translation
Why it matters
This platform provides a scalable, low-field magnetic control framework for adaptive microrobotics, advancing safe and versatile navigation and manipulation in confined biomedical environments.
Abstract
Modular small-scale robots offer the potential for on-demand assembly and disassembly, enabling task-specific adaptation in dynamic and constrained environments. How- ever, existing modular magnetic platforms often depend on workspace collisions for reconfiguration, employ bulky three- dimensional electromagnetic systems, and lack robust single- module control, which limits their applicability in biomedi- cal settings. In this work, we present a modular magnetic millirobotic platform comprising three cube-shaped modules with embedded permanent magnets, each designed for a distinct functional role: a free module that supports self- assembly and reconfiguration, a fixed module that enables flip-and-walk locomotion, and a gripper module for cargo manipulation. Locomotion and reconfiguration are actuated by programmable combinations of time-varying two-dimensional uniform and gradient magnetic field inputs. Experiments demonstrate closed-loop navigation using real-time vision feed- back and A* path planning, establishing robust single-module control capabilities. Beyond locomotion, the system achieves self-assembly, multimodal transformations, and disassembly at low field strengths. Chain-to-gripper transformations succeeded in 90% of trials, while chain-to-square transformations were less consistent, underscoring the role of module geometry in reconfiguration reliability. These results establish a versatile modular robotic platform capable of multimodal behavior and robust control, suggesting a promising pathway toward scalable and adaptive task execution in confined environments.