How to Train a Cross-Embodiment Robot Navigation Policy with AI Agents

A worked example of an agent running a real ML pipeline behind human approval gates — scene validation, smoke tests, residual RL training, matched-seed evaluation, then packaging the policy for runtime.

• AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
• eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.

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