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 …

Large language models (LLMs) have demonstrated exciting progress in acquiring diverse
new capabilities through in-context learning, ranging from logical reasoning to 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 …

Existing learning-based autonomous driving (AD) systems face challenges in
comprehending high-level information, generalizing to rare events, and providing …

Robotics is an emerging synthetic science concerned with programming work. Robot
technologies are quickly advancing beyond the insights of the existing science. More secure …

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 …

We present a new algorithm for task and motion planning (TMP) and discuss the
requirements and abstractions necessary to obtain robust solutions for TMP in general. Our …

This paper describes a framework for automatically generating optimal action-level behavior
for a team of robots based on temporal logic mission specifications under resource …

We present a new constraint-based framework for task and motion planning (TMP). Our
approach is extensible, probabilistically complete, and offers improved performance and …

General-purpose robots can perform a range of useful tasks in human environments;
however, programming them to robustly function in all possible environments that they might …