PROGrasp: Pragmatic Human-Robot Communication for Object Grasping
Not on the map. Why?
Abstract (arXiv)
Interactive Object Grasping (IOG) is the task of identifying and grasping the desired object via human-robot natural language interaction. Current IOG systems assume that a human user initially specifies the target object's category (e.g., bottle). Inspired by pragmatics, where humans often convey their intentions by relying on context to achieve goals, we introduce a new IOG task, Pragmatic-IOG, and the corresponding dataset, Intention-oriented Multi-modal Dialogue (IM-Dial). In our proposed task scenario, an intention-oriented utterance (e.g., "I am thirsty") is initially given to the robot. The robot should then identify the target object by interacting with a human user. Based on the task setup, we propose a new robotic system that can interpret the user's intention and pick up the target object, Pragmatic Object Grasping (PROGrasp). PROGrasp performs Pragmatic-IOG by incorporating modules for visual grounding, question asking, object grasping, and most importantly, answer interpretation for pragmatic inference. Experimental results show that PROGrasp is effective in offline (i.e., target object discovery) and online (i.e., IOG with a physical robot arm) settings. Code and data are available at https://github.com/gicheonkang/prograsp.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 26 of its 41 references that are in the map. First posted on arXiv 14 Sep 2023.
Builds on
26 of 41 references.
References · 26
- 2017Attention Is All You Needcited by 60,361
- 2014Sequence to Sequence Learning with Neural Networkscited by 2,986
- 2019ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Taskscited by 2,222
- 2021LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairscited by 1,555
- 2019LXMERT: Learning Cross-Modality Encoder Representations from Transformerscited by 1,553
- 2021Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Conceptscited by 1,216
- 2016Modeling Context in Referring Expressionscited by 1,063
- 2017Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environmentscited by 1,027
- 2022OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Frameworkcited by 745
- 2018Speaker-Follower Models for Vision-and-Language Navigationcited by 340
- 2016GuessWhat?! Visual object discovery through multi-modal dialoguecited by 113
- 2014Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Studycited by 89
14 more
- 2016Reasoning About Pragmatics with Neural Listeners and Speakerscited by 68
- 2017Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructionscited by 62
- 2017Colors in Context: A Pragmatic Neural Model for Grounded Language Understandingcited by 57
- 2018Interactive Visual Grounding of Referring Expressions for Human-Robot Interactioncited by 56
- 2018Pragmatically Informative Image Captioning with Character-Level Inferencecited by 42
- 2019Pragmatically Informative Text Generationcited by 32
- 2021INVIGORATE: Interactive Visual Grounding and Grasping in Cluttercited by 32
- 2020Robot Object Retrieval with Contextual Natural Language Queriescited by 26
- 2022Interactive Robotic Grasping with Attribute-Guided Disambiguationcited by 19
- 2020Spatial Reasoning from Natural Language Instructions for Robot Manipulationcited by 16
- 2018Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialogcited by 11
- 2022The Dialog Must Go On: Improving Visual Dialog via Generative Self-Trainingcited by 7
- 2017Grounding Spatio-Semantic Referring Expressions for Human-Robot Interactioncited by 5
- 2023GVCCI: Lifelong Learning of Visual Grounding for Language-Guided Robotic Manipulationcited by 4
Built on by
Citing papers per year: 2023: 1; 2024: 0; 2025: 0; 2026: 1.
2 papers.
- 2026Active Perception for Embodied Disambiguation11 Aug 2026
- 2023PGA: Personalizing Grasping Agents with Single Human-Robot Interaction19 Oct 2023