# A Survey of Language-Based Communication in Robotics

arXiv: https://arxiv.org/abs/2406.04086 · HTML: https://mlsanity.com/paper/2406.04086/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jun 2024.

## Built on by (most cited first, 10 of 10)

- [Large Language Models for Multi-Robot Systems: A Survey](https://mlsanity.com/paper/2502.03814/) (2025)
- [Generative Multi-Agent Collaboration in Embodied AI: A Systematic Review](https://mlsanity.com/paper/2502.11518/) (2025)
- [ConformalNL2LTL: Translating Natural Language Instructions into Temporal Logic Formulas with Conformal Correctness Guarantees](https://mlsanity.com/paper/2504.21022/) (2025)
- [MARLIN: Multi-Agent Reinforcement Learning Guided by Language-Based Inter-Robot Negotiation](https://mlsanity.com/paper/2410.14383/) (2024)
- [ELHPlan: Efficient Long-Horizon Task Planning for Multi-Agent Collaboration](https://mlsanity.com/paper/2509.24230/) (2025)
- [Psychomatics -- A Multidisciplinary Framework for Understanding Artificial Minds](https://mlsanity.com/paper/2407.16444/) (2024)
- [Enforcing Cybersecurity Constraints for LLM-driven Robot Agents for Online Transactions](https://mlsanity.com/paper/2503.15546/) (2025)
- [Trajectory Adaptation using Large Language Models](https://mlsanity.com/paper/2504.12755/) (2025)
- [Hierarchical Policies from Verbal and Egocentric Human Signals for Natural Human-Robot Interaction](https://mlsanity.com/paper/2606.10276/) (2026)
- [A Closed-Loop Multi-Agent Framework for Robust Multi-Robot Manipulation](https://mlsanity.com/paper/2607.06990/) (2026)

## Abstract (arXiv)

Embodied robots which can interact with their environment and neighbours are increasingly being used as a test case to develop Artificial Intelligence. This creates a need for multimodal robot controllers that can operate across different types of information, including text. Large Language Models are able to process and generate textual as well as audiovisual data and, more recently, robot actions. Language Models are increasingly being applied to robotic systems; these Language-Based robots leverage the power of language models in a variety of ways. Additionally, the use of language opens up multiple forms of information exchange between members of a human-robot team. This survey motivates the use of language models in robotics, and then delineates works based on the part of the overall control flow in which language is incorporated. Language can be used by human to task a robot, by a robot to inform a human, between robots as a human-like communication medium, and internally for a robot's planning and control. Applications of language-based robots are explored, and numerous limitations and challenges are discussed to provide a summary of the development needed for the future of language-based robotics.