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Affordances in Robotic Tasks -- A Survey

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arxiv 2004.07400 v1 pith:5WKBMK6F submitted 2020-04-15 cs.RO

Paola Ardón , Èric Pairet , Katrin S. Lohan , Subramanian Ramamoorthy , Ronald P. A. Petrick This is my paper · ORCID
classification cs.RO
keywords affordancesliteratureroboticroboticsdifferentdiscusssurveyaffordance
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Affordances are key attributes of what must be perceived by an autonomous robotic agent in order to effectively interact with novel objects. Historically, the concept derives from the literature in psychology and cognitive science, where affordances are discussed in a way that makes it hard for the definition to be directly transferred to computational specifications useful for robots. This review article is focused specifically on robotics, so we discuss the related literature from this perspective. In this survey, we classify the literature and try to find common ground amongst different approaches with a view to application in robotics. We propose a categorisation based on the level of prior knowledge that is assumed to build the relationship among different affordance components that matter for a particular robotic task. We also identify areas for future improvement and discuss possible directions that are likely to be fruitful in terms of impact on robotics practice.

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Forward citations

Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SurgAM: Surgical Affordance Map Prediction with Multimodal Feature Fusion for Robot Autonomy

    cs.RO 2026-07 conditional novelty 6.0 of 10

    SurgAM fuses DINOv2 semantic features with Stable Diffusion spatial features plus hierarchical prompts to predict surgical affordance maps that enable autonomous phantom tasks.

  2. Token-Based Affordance Grounding with Large Vision-Language Models

    cs.CV 2026-07 accept novelty 6.0 of 10

    TokAG selects the LVLM output token whose aggregated cross-attention is most concentrated on a CLIPSeg object mask, converting that map into a zero-shot affordance heatmap that outperforms weakly supervised baselines.

  3. Affogato: Open-Vocabulary Affordance Grounding with Automated Data Generation at Scale

    cs.CV 2025-06 conditional novelty 6.0 of 10

    A fully automated pipeline using Gemma, Molmo, and SAM generated 750K open-vocabulary 3D affordance annotations on 150K Objaverse objects, and models trained on them transfer to unseen categories.

  4. AffordanceSAM: Segment Anything Once More in Affordance Grounding

    cs.CV 2025-04 conditional novelty 6.0 of 10

    Adapting EVF-SAM with learnable affordance queries and a coarse-to-fine dataset yields strong affordance grounding on AGD20K, with caveats about test-set tuning.

  5. AffordDP: Generalizable Diffusion Policy with Transferable Affordance

    cs.RO 2024-12 conditional novelty 6.0 of 10

    A diffusion-based manipulation policy conditioned on transferred 3D contact points and post-contact trajectories, with adaptive affordance-guided sampling, generalizes to unseen object instances and categories.

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