Persistent robot autonomy requires separating planning, memory, and verification into distinct components rather than relying on a single model; OmniAct demonstrates this approach scales to 100k+ interaction tokens while maintaining performance on real-world tasks.
OmniAct is a framework for building embodied robots that can perform long-horizon tasks in real-world environments by combining planning, memory management, and failure detection.