Test-and-Check is one of ANIMA's defining moves: it turns the claim of task completion into a proposition that must be re-verified. Six gates reject uninterpretable specs before execution; three stages (Pre / Runtime / Post) ensure failure never gets silently papered over.
JSON / intent vocabulary / skill availability / parameter ranges / safety bounds / preconditions — any gate failing rejects the TaskSpec and triggers re-parsing at L1 or a clarification request to the user.
The behavior tree ticks observably: every node status change, every skill call, every failure-and-retry pushes an event toward L5. This catches drift earlier than checking logs after the fact.
Observe the world again: object poses, states, scene changes. Confirm the claim of success before trusting it — otherwise enter retry, rollback, or an explicit natural-language report.
The system never fakes success. Failures route to one of three exits: retry (idempotent actions), graceful degradation (switch to a safer skill), or human handoff (report in natural language and request).
The most concrete reference implementation today
A tabletop language-driven robot arm project used to validate ANIMA's cognition loop, visual grounding, skill execution, and failure recovery.
It is not the final product. It is the benchmark and manipulation capability layer on the path to home robotics.
Medical-care intent-to-action simulation
The medical-care product line of the SOMA family. Powered by the ANIMA cognition framework, it turns intent (text, voice, and future BCI signals) into auditable robot actions inside a simulated hospital ward. v0.4 focuses on showcasing the full intent-to-care loop via MuJoCo simulation and offline video.
The care product line of the SOMA family, running in parallel with soma-arm and sharing the ANIMA cognition framework.