mlsanityData to 14 Oct 2026

Semantics in Robotics: Environmental Data Can't Yield Conventions of Human Behaviour

arXiv 2410.19308 ↗First posted 25 Oct 2024cs.RO cs.AIcited by 0

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Abstract (arXiv)

The word semantics, in robotics and AI, has no canonical definition. It usually serves to denote additional data provided to autonomous agents to aid HRI. Most researchers seem, implicitly, to understand that such data cannot simply be extracted from environmental data. I try to make explicit why this is so and argue that so-called semantics are best understood as data comprised of conventions of human behaviour. This includes labels, most obviously, but also places, ontologies, and affordances. Object affordances are especially problematic because they require not only semantics that are not in the environmental data (conventions of object use) but also an understanding of physics and object combinations that would, if achieved, constitute artificial superintelligence.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 97 references that are in the map. First posted on arXiv 25 Oct 2024.

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15 of 97 references.

References · 15

  1. 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,348
  2. 2022Visual Language Maps for Robot Navigationcited by 365
  3. 2018Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objectscited by 241
  4. 2017AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detectioncited by 128
  5. 20206G Networks: Beyond Shannon Towards Semantic and Goal-Oriented Communicationscited by 112
  6. 2020From Semantic Communication to Semantic-aware Networking: Model, Architecture, and Open Problemscited by 52
  7. 2023The Vector Grounding Problemcited by 39
  8. 2020Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented Graspingcited by 27
  9. 2019Learning Grasp Affordance Reasoning through Semantic Relationscited by 23
  10. 2018Visual Affordance and Function Understanding: A Surveycited by 20
  11. 2021Semantic-Based Explainable AI: Leveraging Semantic Scene Graphs and Pairwise Ranking to Explain Robot Failurescited by 13
  12. 2021Towards Goal-Oriented Semantic Signal Processing: Applications and Future Challengescited by 11
3 more
  1. 2019CAGE: Context-Aware Grasping Enginecited by 10
  2. 2024Tell Me Where You Are: Multimodal LLMs Meet Place Recognitioncited by 7
  3. 2019From Multi-modal Property Dataset to Robot-centric Conceptual Knowledge About Household Objectscited by 3

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