
The breakthrough eliminates the reliability‑adaptability trade‑off that has limited modular robotics, enabling autonomous systems that stay operational despite individual component failures. It also paves the way for self‑sustaining robot swarms, reducing downtime in industrial, exploration, and disaster‑response scenarios.
Modular robotics promises versatile machines that can reconfigure for diverse tasks, yet each added unit introduces a new point of failure. Traditional designs rely on isolated power supplies and sensors, so a single malfunction can cripple the entire system. This reliability gap has constrained adoption in sectors such as logistics, infrastructure inspection, and planetary exploration, where uninterrupted operation is critical.
The EPFL team tackled the problem with a concept they call hyper‑redundancy, which distributes power, communication, and sensing capabilities across every module in real time. In a controlled locomotion test, the four‑piece Mori3 robot lost all resources in its central module, a condition that would normally halt movement. By allowing neighboring modules to share their own resources, the robot not only kept walking but also reshaped itself to pass under an obstacle, effectively “reviving” the dead unit. The results, published in Science Robotics, demonstrate a clear reversal of the failure‑rate curve as the number of modules increases.
Looking ahead, this collective‑resource model could transform swarm robotics, where dozens or hundreds of small agents operate together. If each robot can dock and exchange energy or data on demand, fleets become self‑healing and far less dependent on external charging stations or centralized control. Industries ranging from warehouse automation to offshore maintenance stand to benefit from robots that maintain functionality despite harsh environments or component wear, potentially lowering operational costs and extending mission lifespans.
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