182 citations · 874 across the 39 of their papers we have counts for
23 papers · 1 filter
"Tidy Up the Table": Grounding Common-sense Objective for Tabletop Object Rearrangement
Yiqing Xu, David Hsu
Tidying up a messy table may appear simple for humans, but articulating clear criteria for tidiness is challenging due to the ambiguous nature of common sense reasoning. Large Lang…
Large Language Models as Commonsense Knowledge for Large-Scale Task Planning
Zirui Zhao, Wee Sun Lee, David Hsu
Large-scale task planning is a major challenge. Recent work exploits large language models (LLMs) directly as a policy and shows surprisingly interesting results. This paper shows…
DaXBench: Benchmarking Deformable Object Manipulation with Differentiable Physics
Siwei Chen, Yiqing Xu, Cunjun Yu +4
Deformable Object Manipulation (DOM) is of significant importance to both daily and industrial applications. Recent successes in differentiable physics simulators allow learning al…
Differentiable Parsing and Visual Grounding of Natural Language Instructions for Object Placement
Zirui Zhao, Wee Sun Lee, David Hsu
We present a new method, PARsing And visual GrOuNding (ParaGon), for grounding natural language in object placement tasks. Natural language generally describes objects and spatial…
Partially Observable Markov Decision Processes in Robotics: A Survey
Mikko Lauri, David Hsu, Joni Pajarinen
Noisy sensing, imperfect control, and environment changes are defining characteristics of many real-world robot tasks. The partially observable Markov decision process (POMDP) prov…
INVIGORATE: Interactive Visual Grounding and Grasping in Clutter
Hanbo Zhang, Yunfan Lu, Cunjun Yu +3
This paper presents INVIGORATE, a robot system that interacts with human through natural language and grasps a specified object in clutter. The objects may occlude, obstruct, or ev…