Visual affordance and function understanding: A survey

M Hassanin, S Khan, M Tahtali - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Nowadays, robots are dominating the manufacturing, entertainment, and healthcare
industries. Robot vision aims to equip robots with the capabilities to discover information …

Adaafford: Learning to adapt manipulation affordance for 3d articulated objects via few-shot interactions

Y Wang, R Wu, K Mo, J Ke, Q Fan, LJ Guibas… - European conference on …, 2022 - Springer
Perceiving and interacting with 3D articulated objects, such as cabinets, doors, and faucets,
pose particular challenges for future home-assistant robots performing daily tasks in human …

O2o-afford: Annotation-free large-scale object-object affordance learning

K Mo, Y Qin, F Xiang, H Su… - Conference on robot …, 2022 - proceedings.mlr.press
Contrary to the vast literature in modeling, perceiving, and understanding agent-object (eg,
human-object, hand-object, robot-object) interaction in computer vision and robotics, very …

A survey of knowledge representation in service robotics

D Paulius, Y Sun - Robotics and Autonomous Systems, 2019 - Elsevier
Within the realm of service robotics, researchers have placed a great amount of effort into
learning, understanding, and representing motions as manipulations for task execution by …

Affordances in robotic tasks--a survey

P Ardón, È Pairet, KS Lohan, S Ramamoorthy… - arXiv preprint arXiv …, 2020 - arxiv.org
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 …

Interacting objects: A dataset of object-object interactions for richer dynamic scene representations

A Unmesh, R Jain, J Shi, VKC Manam… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
Dynamic environments in factories, surgical robotics, and warehouses increasingly involve
humans, machines, robots, and various other objects such as tools, fixtures, conveyors, and …

Approximate task tree retrieval in a knowledge network for robotic cooking

MS Sakib, D Paulius, Y Sun - IEEE Robotics and Automation …, 2022 - ieeexplore.ieee.org
Flexible task planning continues to pose a difficult challenge for robots, where a robot is
unable to creatively adapt their task plans to new or unseen problems, which is mainly due …

Functional object-oriented network for manipulation learning

D Paulius, Y Huang, R Milton… - 2016 IEEE/RSJ …, 2016 - ieeexplore.ieee.org
This paper presents a novel structured knowledge representation called the functional
object-oriented network (FOON) to model the connectivity of the functional-related objects …

From cooking recipes to robot task trees–improving planning correctness and task efficiency by leveraging llms with a knowledge network

MS Sakib, Y Sun - 2024 IEEE International Conference on …, 2024 - ieeexplore.ieee.org
Task planning for robotic cooking involves generating a sequence of actions for a robot to
prepare a meal successfully. This paper introduces a novel task tree generation pipeline …

Regrad: A large-scale relational grasp dataset for safe and object-specific robotic grasping in clutter

H Zhang, D Yang, H Wang, B Zhao… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
Despite the impressive progress achieved in robotic grasping, robots are not skilled in
sophisticated tasks (eg search and grasp a specified target in clutter). Such tasks involve not …