The Unstoppable Modular Robot
By sharing power and data across modules, researchers have created robots that get more reliable — not less — as they become more complex.
The more complex a machine is, the more it is capable of doing. While this is generally true, anyone who has opted to purchase the most feature-packed vehicle, appliance, or electronic gadget knows that it also means there are more things to break. All of this additional convenience tends to come with headaches like poor reliability and hefty repair bills.
Things are much the same in the world of robotics. Traditional designs split functions into separate components. If one of these components breaks, the functionality it provides is gone. But there may be a better way to build robots, says a team of engineers at the Swiss Federal Technology Institute of Lausanne. They have developed a method that makes it possible for resources to be shared between components, allowing failures in one area to be compensated for by resources in another area.
The researchers focused on modular robots—machines built from multiple smaller units that connect together to form a larger system. These robots are attractive because they can change shape, adapt to different tasks, and continue operating even if part of their structure is damaged. Historically, however, they have suffered from a major drawback: every additional module adds more potential points of failure.
Instead of adding backup hardware to each unit, the team pursued a different philosophy. They allowed the modules to share essential resources directly with their neighbors. Power, communication, and sensor data are no longer confined to a single module. Instead, they flow across the entire robot collective, a strategy the engineers call “local resource sharing” and “hyper-redundancy.”
To test the concept, they used a modular origami-style robot called Mori3, built from four triangular units. The team intentionally disabled the central module by cutting off its battery power, sensors, and wireless communication—conditions that would normally immobilize the machine. Instead, the surrounding modules supplied the missing resources. The robot still managed to walk across uneven terrain and squeeze under a barrier, effectively reviving the disabled component.
Surprisingly, the results showed that reliability improved as more modules were added, reversing the usual engineering trade-off between adaptability and durability. Sharing only one resource was not enough, but sharing all critical resources together allowed the system to compensate for failures automatically.
The researchers believe the approach could eventually extend beyond modular robots to entire robotic swarms. Future machines might dock together to exchange energy and information, allowing groups of robots to continue operating even when individual members are damaged.