1. Introduction
2. Robotics Based on LLMs
2.1. Language Model Overview
2.2. Benefits of LLM for Robotics
2.3. Robotics Based on LLMs
2.4. New Transformer Architecture for Robotics
3. Related Technologies
3.1. Perception
3.2. Decision-making
3.3. Control
3.4. Interaction
4. Applications of LLMs in Robotics
5. Challenges
5.1. Datasets
5.2. Training Schemes
5.3. Shape
5.4. LLM Deployment
5.5. Security
5.6. Dialogue Consistency
5.7. Social Influence
5.8. Ethics
6. Promising Directions for Future Work
6.1. Security of Task Execution
6.2. Training Scenario Transfer
6.3. Unify Format of Modal
6.4. Modular Components
6.5. Autonomous Perception
7. Conclusions