Fault tolerance
Related papers: 20
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Fault tolerance in robotics and AI refers to a system's ability to continue operating correctly — or degrade gracefully — when one or more of its components fail, malfunction, or produce unexpected outputs. This encompasses hardware failures such as actuator or sensor damage, software errors, communication dropouts, and unpredictable environmental conditions. In robotics, fault tolerance is implemented through strategies including redundant subsystems, real-time fault detection and estimation, reconfigurable control architectures, and adaptive algorithms that compensate for identified faults. Multi-robot systems leverage it through distributed task reallocation, where functioning robots absorb the responsibilities of failed teammates, as seen in architectures like ALLIANCE. For individual manipulators or autonomous vehicles, sliding mode controllers, neural networks, and adaptive estimators can detect and accommodate actuator faults mid-operation. Fault tolerance matters because real-world deployments — whether in manufacturing, space exploration, agriculture, or disaster response — demand reliability without constant human intervention. As robotic systems grow more autonomous and safety-critical, building in fault tolerance is essential to ensuring mission success, protecting hardware, and maintaining safety around humans.
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