Grounding

[IROS-24] Lang2LTL-2: Grounding Spatiotemporal Navigation Commands Using Large Language and Vision-Language Models

TL;DR – Building on prior work (Lang2LTL - CoRL 2023), this paper introduces a modular system that enables robots to follow natural language commands with spatiotemporal referring expressions. This system leverages multi-modal foundation models as well as linear temporal logic.

Rationing and frictional unemployment in the United States, 1964–2009

[RAL-23] Long-Horizon Planning and Execution with Functional Object-Oriented Networks

TL;DR – In this paper, we introduce the idea of connecting FOONs to robotic task and motion planning. We automatically transform a FOON graph, which exists at the object level (i.e., it is a representation that uses meaningful labels or expressions close to human language), into task planning specifications written in PDDL (not a very intuitive way to communicate about tasks).