Skill-SLM: Agent Skill-driven Small Language Models for Reliable Robot Operation
Skill-SLM reframes robot operation as decomposing tasks into subtasks and composing them using learned skills. It builds a skill library via a grammar, uses two agents for decomposition and orchestration, and employs progressive orchestration to ensure coherent, reliable robot actions. This method outperforms distillation-based approaches on unseen tasks.