Researchers have developed “link-bots”—modular, self-propelled chains that achieve complex group behaviors using only basic geometric connections and vibration.
Study: Emergent functional dynamics of link-bots. Image Credit: AlesiaKan/Shutterstock.com
In a recent Science Advances article, the team introduced V-shaped, synthetic active chains that demonstrate collective behaviors like movement, navigation, and object manipulation through straightforward physical interactions. These modular bots rely on simple linking mechanisms rather than complex components. By tweaking a few key parameters, they can traverse spaces and transport loads, offering a minimalist yet effective approach to programmable soft robotics inspired by natural active matter.
Background
Active collectives, whether biological or synthetic, achieve complex tasks through group dynamics. Many synthetic systems today either depend on individuals with sophisticated onboard computing or require external stimuli like light or magnetic fields. These approaches can limit scalability and adaptability.
To address these challenges, recent research has shifted toward systems where behaviors emerge from physical interactions. However, many of these setups, such as granular materials or connected robot chains, lack versatility or responsiveness to their environment.
This study presents a different approach. The researchers developed "link-bots," simple, self-propelled bots connected by joints that limit their movement angles. Their collective behavior emerges purely from these geometric constraints. Without needing external control or complex programming, link-bots can move, navigate obstacles, and transport objects. The work demonstrates a practical path toward programmable active matter with broad potential in soft robotics and autonomous systems.
Methods and Modeling
Each link-bot was 3D-printed with a cylindrical body, tilted legs, and a cuboid top. The bots were connected using specially designed links with notches to restrict movement angles. Fabrication was done via high-resolution stereolithography.
The bots operated on a level circular platform that vibrated vertically at 80 Hz with a 70-micrometer amplitude. This setup activated the bots’ motion.
To complement the experiments, the team created a Python-based simulation. Each bot was modeled as an active Brownian particle, with position and orientation updated based on self-propulsion speed and random noise. The simulation accounted for key physical constraints: spring-like forces maintained link rigidity, and the notched joints enforced angular limits. Bots at the center of a chain experienced dual constraints, resulting in more complex dynamics.
The simulations replicated behaviors seen in experiments—such as rhythmic "breathing" motions and side-chain "flapping" near boundaries—allowing the researchers to explore how simple physical rules could generate sophisticated group dynamics.
Key Findings
Individually, each 1.5 cm bot moved at around 8 cm/second when activated by vibration, displaying typical active Brownian motion. But when linked together, the bots behaved in strikingly coordinated ways.
Depending on the linking angles, the bots displayed two dynamic modes: "breathing" (oscillations in the central link angles) and "flapping" (bending at the side chains). These modes produced distinct gaits when the bots encountered boundaries—either continuous motion, oscillation, or stalling.
Link-bots with smaller linking angles were better at exploration, moving through narrow gaps or winding channels, while those with wider angles excelled at tasks like blocking openings or hugging walls. Asymmetric setups allowed the bots to steer around curved obstacles.
The bots also showed the ability to transport objects. Shorter, more flexible chains could carry loads forward, while longer, stiffer configurations pushed or maneuvered around them.
Interestingly, social dynamics also emerged. Pairs of bots could work together to pass through tight spaces—if aligned properly—or get stuck in competitive jams. All of this occurred without central coordination, driven solely by geometry and vibration.
Both the experiments and simulations confirmed that these behaviors scale effectively with system size, highlighting the potential for deploying such systems in real-world environments.
Conclusion
This research illustrates how simple geometric constraints can give rise to complex, coordinated behaviors in modular robot systems. Link-bots, built from self-propelled units and connected by movement-limiting joints, can navigate, transport, and respond to their environment—all without centralized control or complex code.
While the system depends on vibration in its current form, the core principle, emergence through steric interaction, offers a promising foundation for scalable soft robotics. Future work could explore dynamic links that adjust in real-time, opening up even more applications in areas like search-and-rescue, surveillance, and lightweight logistics.
The link-bot platform points to a resource-efficient strategy for building adaptive, autonomous machines capable of complex tasks with surprisingly simple rules.
Journal Reference
Son, K., Bowal, K., Kim, K., Mahadevan, L., & Kim, H.-Y. (2025). Emergent functional dynamics of link-bots. Science Advances, 11(19). DOI:10.1126/sciadv.adu8326. https://www.science.org/doi/10.1126/sciadv.adu8326
Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.