mlsanityData to 7 Oct 2026

Reasoning with Scene Graphs for Robot Planning under Partial Observability

arXiv 2202.10432 ↗First posted 21 Feb 2022cs.RO cs.AIcited by 25

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Abstract (arXiv)

Robot planning in partially observable domains is difficult, because a robot needs to estimate the current state and plan actions at the same time. When the domain includes many objects, reasoning about the objects and their relationships makes robot planning even more difficult. In this paper, we develop an algorithm called scene analysis for robot planning (SARP) that enables robots to reason with visual contextual information toward achieving long-term goals under uncertainty. SARP constructs scene graphs, a factored representation of objects and their relations, using images captured from different positions, and reasons with them to enable context-aware robot planning under partial observability. Experiments have been conducted using multiple 3D environments in simulation, and a dataset collected by a real robot. In comparison to standard robot planning and scene analysis methods, in a target search domain, SARP improves both efficiency and accuracy in task completion. Supplementary material can be found at https://tinyurl.com/sarp22

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 22 of its 52 references that are in the map. First posted on arXiv 21 Feb 2022.

Builds on

22 of 52 references.

References · 22

  1. 2016Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotationscited by 2,646
  2. 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 850
  3. 2017Scene Graph Generation by Iterative Message Passingcited by 462
  4. 2017Neural Motifs: Scene Graph Parsing with Global Contextcited by 413
  5. 2019GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representationscited by 227
  6. 2020SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decompositioncited by 190
  7. 2019Knowledge-Embedded Routing Network for Scene Graph Generationcited by 163
  8. 2017Scene Graph Generation from Objects, Phrases and Region Captionscited by 154
  9. 20203D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humanscited by 141
  10. 2020Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphscited by 83
  11. 2018PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Makingcited by 51
  12. 2019Bayesian Relational Memory for Semantic Visual Navigationcited by 48
10 more
  1. 2020Semantic Linking Maps for Active Visual Object Searchcited by 18
  2. 2016The STRANDS Project: Long-Term Autonomy in Everyday Environmentscited by 13
  3. 2015REBA: A Refinement-Based Architecture for Knowledge Representation and Reasoning in Roboticscited by 10
  4. 2020Spatial Language Understanding for Object Search in Partially Observed City-scale Environmentscited by 7
  5. 2022Incremental Object Grounding Using Scene Graphscited by 6
  6. 2019Learning and Reasoning for Robot Sequential Decision Making under Uncertaintycited by 5
  7. 2020Semantic Task Planning for Service Robots in Open Worldcited by 5
  8. 2020A Survey of Knowledge-based Sequential Decision Making under Uncertaintycited by 4
  9. 2018Integrating Human-Provided Information Into Belief State Representation Using Dynamic Factorizationcited by 2
  10. 2021Learning to Guide Human Attention on Mobile Telepresence Robots with 360 Visioncited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 12; 2024: 7; 2025: 3; 2026: 1.

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  1. 2022Panoptic Scene Graph Generationcited by 114
  2. 2024Learning Generalizable Feature Fields for Mobile Manipulationcited by 31
  3. 20244D Panoptic Scene Graph Generationcited by 22
  4. 2023pgmpy: A Python Toolkit for Bayesian Networkscited by 21
  5. 2023Modeling Dynamic Environments with Scene Graph Memorycited by 18
  6. 2023TextPSG: Panoptic Scene Graph Generation from Textual Descriptionscited by 14
  7. 2023Cross-Modality Time-Variant Relation Learning for Generating Dynamic Scene Graphscited by 13
  8. 2023HOI4ABOT: Human-Object Interaction Anticipation for Human Intention Reading Collaborative roBOTscited by 12
  9. 2023VLPrompt: Vision-Language Prompting for Panoptic Scene Graph Generationcited by 12
  10. 2023Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledgecited by 7
  11. 2024VeriGraph: Scene Graphs for Execution Verifiable Robot Planningcited by 7
  12. 2023JaSPICE: Automatic Evaluation Metric Using Predicate-Argument Structures for Image Captioning Modelscited by 6
13 more
  1. 2024Scene-Graph ViT: End-to-End Open-Vocabulary Visual Relationship Detectioncited by 6
  2. 2024Weakly-Supervised 3D Scene Graph Generation via Visual-Linguistic Assisted Pseudo-labelingcited by 5
  3. 2024SceneLLM: Implicit Language Reasoning in LLM for Dynamic Scene Graph Generationcited by 5
  4. 2023Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph Generationcited by 4
  5. 2024Belief Scene Graphs: Expanding Partial Scenes with Objects through Computation of Expectationcited by 4
  6. 20233D Scene Graph Prediction on Point Clouds Using Knowledge Graphscited by 3
  7. 2025Imagine, Verify, Execute: Memory-guided Agentic Exploration with Vision-Language Modelscited by 2
  8. 2023Task-Driven Graph Attention for Hierarchical Relational Object Navigationcited by 1
  9. 2025FORESCENE: FOREcasting human activity via latent SCENE graphs diffusioncited by 1
  10. 2022SGDraw: Scene Graph Drawing Interface Using Object-Oriented Representationcited by 0
  11. 2023STDG: Semi-Teacher-Student Training Paradigram for Depth-guided One-stage Scene Graph Generationcited by 0
  12. 2025FOGMACHINE -- Leveraging Discrete-Event Simulation and Scene Graphs for Modeling Hierarchical, Interconnected Environments under Partial Observations from Mobile Agentscited by 0
  13. 2026GAVEL: Graph World Models for Verified and Efficient Long-Horizon LLM Task Planningcited by 0