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Dialogue Object Search

arXiv 2107.10653 ↗First posted 22 Jul 2021cs.RO cs.AIcited by 0

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Abstract (arXiv)

We envision robots that can collaborate and communicate seamlessly with humans. It is necessary for such robots to decide both what to say and how to act, while interacting with humans. To this end, we introduce a new task, dialogue object search: A robot is tasked to search for a target object (e.g. fork) in a human environment (e.g., kitchen), while engaging in a "video call" with a remote human who has additional but inexact knowledge about the target's location. That is, the robot conducts speech-based dialogue with the human, while sharing the image from its mounted camera. This task is challenging at multiple levels, from data collection, algorithm and system development,to evaluation. Despite these challenges, we believe such a task blocks the path towards more intelligent and collaborative robots. In this extended abstract, we motivate and introduce the dialogue object search task and analyze examples collected from a pilot study. We then discuss our next steps and conclude with several challenges on which we hope to receive feedback.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 18 references that are in the map. First posted on arXiv 22 Jul 2021.

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12 of 18 references.

References · 12

  1. 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 850
  2. 2016Visual Dialogcited by 377
  3. 2016A Network-based End-to-End Trainable Task-oriented Dialogue Systemcited by 252
  4. 2019Vision-and-Dialog Navigationcited by 246
  5. 2020ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objectscited by 240
  6. 2017IQA: Visual Question Answering in Interactive Environmentscited by 154
  7. 2018Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learningcited by 91
  8. 2018Talk the Walk: Navigating New York City through Grounded Dialoguecited by 44
  9. 2018On Evaluating and Comparing Open Domain Dialog Systemscited by 16
  10. 2020Multi-Resolution POMDP Planning for Multi-Object Search in 3Dcited by 8
  11. 2020Spatial Language Understanding for Object Search in Partially Observed City-scale Environmentscited by 7
  12. 2021Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graphcited by 7

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