Part 2: LLM‑Powered Humanoid Robots - From Hype to Factory Floor
- Tetsu Yamaguchi
- 6 days ago
- 1 min read
Updated: 5 days ago
Industrial humanoids are finally moving off demo stages and into pilot work‑cells. The missing ingredient is a cognitive stack that can juggle perception, long‑horizon planning, and real‑time control on constrained compute. Here’s how 2025’s LLM tech lines up.
Factory Pain‑Point | 2025 Technique | Proof‑of‑Concepts |
Long multi‑step manipulation (pick → re‑grasp → insert) | Long‑context windows + MemGPT‑style memory keep >20 sub‑goals alive. | ELLMER executes 17‑step assembly tasks on a Fanuc CRX‑25iA. |
Rapid skill authoring by line engineers | Retrieval‑Augmented Generation 2.0 mines a knowledge base of ROS2 recipes; Dynamic LoRA compiles chat instructions into runnable nodes in seconds. | Alchemist IDE beta (ABB Robotics). |
Real‑time inference in a 200 Hz control loop | SSM backbones + INT4 + 2:4 sparsity run on a single Jetson Orin‑NX. | IBM Bamba‑Tiny‑6Bdemo on Unitree H1. |
One robot, many skills (balance, stairs, peg‑in‑hole) | Mixture‑of‑Experts routes tokens to locomotion vs manipulation specialists. | NVIDIA Isaac GR00T N1with 64 experts. |
Bridging sim‑to‑real & safety sign‑off | World‑Model co‑training: planner proposes, simulator vetoes unsafe trajectories. | Boston Dynamics Atlas @ Hyundai production trials. |
Sub‑ms collision/risk monitoring | In‑loop guardrails rewrite or halt unsafe torque commands. | Meta Llama Guard‑Motionresearch prototype. |
Stack in one sentence: Lean SSM core → MoE skill heads → Memory paging → Guardrail filter, all embedded in ROS2.
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