mlsanityData to 7 Oct 2026

Naming Objects for Vision-and-Language Manipulation

arXiv 2303.02871 ↗First posted 6 Mar 2023cs.RO cs.AI cs.HCcited by 1

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Abstract (arXiv)

Robot manipulation tasks by natural language instructions need common understanding of the target object between human and the robot. However, the instructions often have an interpretation ambiguity, because the instruction lacks important information, or does not express the target object correctly to complete the task. To solve this ambiguity problem, we hypothesize that "naming" the target objects in advance will reduce the ambiguity of natural language instructions. We propose a robot system and method that incorporates naming with appearance of the objects in advance, so that in the later manipulation task, instruction can be performed with its unique name to disambiguate the objects easily. To demonstrate the effectiveness of our approach, we build a system that can memorize the target objects, and show that naming the objects facilitates detection of the target objects and improves the success rate of manipulation instructions. With this method, the success rate of object manipulation task increases by 31% in ambiguous instructions.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 18 of its 30 references that are in the map. First posted on arXiv 6 Mar 2023.

Builds on

18 of 30 references.

References · 18

  1. 2019Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learningcited by 1,168
  2. 2021Grounded Language-Image Pre-trainingcited by 1,147
  3. 2015Generation and Comprehension of Unambiguous Object Descriptionscited by 897
  4. 2021MDETR -- Modulated Detection for End-to-End Multi-Modal Understandingcited by 811
  5. 2019ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Taskscited by 773
  6. 2021CLIPort: What and Where Pathways for Robotic Manipulationcited by 617
  7. 2021CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Taskscited by 564
  8. 2022BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learningcited by 517
  9. 2018GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wildcited by 471
  10. 2022VIMA: General Robot Manipulation with Multimodal Promptscited by 403
  11. 2022MixFormer: End-to-End Tracking with Iterative Mixed Attentioncited by 278
  12. 2021FILM: Following Instructions in Language with Modular Methodscited by 119
6 more
  1. 2021Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Cluttercited by 94
  2. 2020Unseen Object Instance Segmentation for Robotic Environmentscited by 85
  3. 2022VLMbench: A Compositional Benchmark for Vision-and-Language Manipulationcited by 68
  4. 2017Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructionscited by 61
  5. 2022Interactive Robotic Grasping with Attribute-Guided Disambiguationcited by 19
  6. 2021Target-dependent UNITER: A Transformer-Based Multimodal Language Comprehension Model for Domestic Service Robotscited by 7

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Citing papers per year: 2023: 1.

1 paper.