Self-Assessment of Grasp Affordance Transfer

Paola Ardon, Èric Pairet Artau, Yvan Petillot, Ronald P. A. Petrick, Subramanian Ramamoorthy, Katrin Solveig Lohan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)
44 Downloads (Pure)


Reasoning about object grasp affordances allows an autonomous agent to estimate the most suitable grasp to execute a task. While current approaches for estimating grasp affordances are effective, their prediction is driven by hypotheses on visual features rather than an indicator of a proposal's suitability for an affordance task. Consequently, these works cannot guarantee any level of performance when executing a task and, in fact, not even ensure successful task completion. In this work, we present a pipeline for self-assessment of grasp affordance transfer (SAGAT) based on prior experiences. We visually detect a grasp affordance region to extract multiple grasp affordance configuration candidates. Using these candidates, we forward simulate the outcome of executing the affordance task to analyse the relation between task outcome and grasp candidates. The relations are ranked by performance success with a heuristic confidence function and used to build a library of affordance task experiences. The library is later queried to perform one-shot transfer estimation of the best grasp configuration on new objects. Experimental evaluation shows that our method exhibits a significant performance improvement up to 11.7% against current state-of-the-art methods on grasp affordance detection. Experiments on a PR2 robotic platform demonstrate our method's highly reliable deployability to deal with real-world task affordance problems.
Original languageEnglish
Title of host publication2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Number of pages8
ISBN (Electronic)9781728162126
Publication statusPublished - 10 Feb 2021
Event2020 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, United States
Duration: 25 Oct 202029 Oct 2020


Conference2020 IEEE/RSJ International Conference on Intelligent Robots and Systems
Abbreviated titleIROS 2020
Country/TerritoryUnited States
CityLas Vegas
Internet address

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications


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