This article surveys the use of natural language in robotics from a robotics point of view. To
use human language, robots must map words to aspects of the physical world, mediated by …

In this paper, an overview of human–robot interactive communication is presented, covering
verbal as well as non-verbal aspects. Following a historical introduction, and motivation …

Large language models (LLMs) trained on code-completion have been shown to be capable
of synthesizing simple Python programs from docstrings [1]. We find that these code-writing …

For effective human-robot interaction, robots need to understand, plan, and execute
complex, long-horizon tasks described by natural language. Recent advances in large …

This paper describes a new model for understanding natural language commands given to
autonomous systems that perform navigation and mobile manipulation in semi-structured …

The context in which language is used provides a strong signal for learning to recover its
meaning. In this paper, we show it can be used within a grounded CCG semantic parsing …

As robots become more ubiquitous and capable of performing complex tasks, the
importance of enabling untrained users to interact with them has increased. In response …

Speaking using unconstrained natural language is an intuitive and flexible way for humans
to interact with robots. Understanding this kind of linguistic input is challenging because …

We address the problem of teaching a deep reinforcement learning (RL) agent to follow
instructions in multi-task environments. Instructions are expressed in a well-known formal …

Reinforcement Learning (RL) algorithms are capable of learning effective behaviours
through trial and error interactions with their environment [40]. The recent combination of …