{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T14:15:10Z","timestamp":1756995310518,"version":"3.28.0"},"reference-count":47,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T00:00:00Z","timestamp":1685318400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T00:00:00Z","timestamp":1685318400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,29]]},"DOI":"10.1109\/icra48891.2023.10161371","type":"proceedings-article","created":{"date-parts":[[2023,7,4]],"date-time":"2023-07-04T13:20:56Z","timestamp":1688476856000},"page":"7279-7286","source":"Crossref","is-referenced-by-count":3,"title":["Self-Supervised Learning of Action Affordances as Interaction Modes"],"prefix":"10.1109","author":[{"given":"Liquan","family":"Wang","sequence":"first","affiliation":[{"name":"University of Toronto &#x0026; Vector Institute,Canada"}]},{"given":"Nikita","family":"Dvornik","sequence":"additional","affiliation":[{"name":"Nvidia,United States"}]},{"given":"Rafael","family":"Dubeau","sequence":"additional","affiliation":[{"name":"University of Toronto &#x0026; Vector Institute,Canada"}]},{"given":"Mayank","family":"Mittal","sequence":"additional","affiliation":[{"name":"ETH Zurich,Switzerland"}]},{"given":"Animesh","family":"Garg","sequence":"additional","affiliation":[{"name":"University of Toronto &#x0026; Vector Institute,Canada"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2012.6224929"},{"key":"ref35","article-title":"O2O-Afford: Annotation-free large-scale object-object affordance learning","author":"mo","year":"0","journal-title":"Conference on Robot Learning (CoRL)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-52991-8_9"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7139369"},{"journal-title":"Screwnet Category-independent articulation model estimation from depth images using screw theory","year":"2020","author":"jain","key":"ref15"},{"journal-title":"Convolutional occupancy networks","year":"2020","author":"peng","key":"ref37"},{"journal-title":"Learning hybrid object kinematics for efficient hierarchical planning under uncertainty","year":"2019","author":"jain","key":"ref14"},{"journal-title":"Synergies between affordance and geometry 6-dof grasp detection via implicit representations","year":"2021","author":"jiang","key":"ref36"},{"journal-title":"Temporally abstract partial models","year":"2021","author":"khetarpal","key":"ref31"},{"journal-title":"Dex-Net 2 0 Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics","year":"2017","author":"mahler","key":"ref30"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2008.4543222"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9560841"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2010.5650927"},{"journal-title":"What can i do here? a theory of affordances in reinforcement learning","year":"2020","author":"khetarpal","key":"ref32"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2010.5649847"},{"key":"ref1","first-page":"1289","article-title":"Learning to generalize kinematic models to novel objects","volume":"100","author":"abbatematteo","year":"0","journal-title":"Proceedings of the Conference on Robot Learning"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2010.5649847"},{"key":"ref39","article-title":"Learning structured output representation using deep conditional generative models","volume":"28","author":"sohn","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref16","first-page":"1289","article-title":"Learning to generalize kinematic models to novel objects","volume":"100","author":"abbatematteo","year":"0","journal-title":"Proceedings of the Conference on Robot Learning"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.29"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7139369"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-79547-6_42"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3349537.3351898"},{"journal-title":"Diversity is all you need Learning skills without a reward function","year":"2018","author":"eysenbach","key":"ref46"},{"journal-title":"What can i do here? a theory of affordances in reinforcement learning","year":"2020","author":"khetarpal","key":"ref23"},{"journal-title":"Behavior from the void Unsupervised active pre-training","year":"2021","author":"liu","key":"ref45"},{"journal-title":"Gift Generalizable interaction-aware functional tool affordances without labels","year":"2021","author":"turpin","key":"ref26"},{"journal-title":"kpam Keypoint affordances for category-level robotic manipulation","year":"2019","author":"manuelli","key":"ref25"},{"journal-title":"Pointnet++ Deep hierarchical feature learning on point sets in a metric space","year":"2017","author":"qi","key":"ref47"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2010.08.002"},{"journal-title":"Urlb Unsupervised reinforcement learning benchmark","year":"2021","author":"laskin","key":"ref42"},{"key":"ref41","article-title":"Isaac gym: High performance gpu-based physics simulation for robot learning","author":"makoviychuk","year":"2021","journal-title":"ArXiv Preprint"},{"journal-title":"Learning affordance landscapes for interaction exploration in 3d environments","year":"2020","author":"nagarajan","key":"ref22"},{"journal-title":"Reinforcement learning with prototypical representations","year":"2021","author":"yarats","key":"ref44"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2015.2396014"},{"journal-title":"Cic Contrastive intrinsic control for unsupervised skill discovery","year":"2022","author":"laskin","key":"ref43"},{"journal-title":"Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision[C]","year":"2018","author":"fang","key":"ref28"},{"journal-title":"Keto Learning keypoint representations for tool manipulation","year":"2019","author":"qin","key":"ref27"},{"journal-title":"Contact-GraspNet Efficient 6-DoF Grasp Generation in Cluttered Scenes","year":"2021","author":"sundermeyer","key":"ref29"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460902"},{"key":"ref7","article-title":"Vat-mart: Learning visual action trajectory proposals for manipulating 3d articulated objects","author":"wu","year":"2022","journal-title":"ICLRE"},{"key":"ref9","article-title":"Umpnet: Universal manipulation policy network for articulated objects","author":"xu","year":"2022","journal-title":"IEEE RA-L"},{"key":"ref4","first-page":"67","article-title":"The theory of affordances","author":"gibson","year":"1977","journal-title":"Perceiving Acting and Knowing Toward an Ecological Psychology"},{"journal-title":"Artic-ulated object interaction in unknown scenes with whole-body mobile manipulation","year":"2022","author":"mittal","key":"ref3"},{"journal-title":"Where2act From pixels to actions for articulated 3d objects","year":"2021","author":"mo","key":"ref6"},{"journal-title":"The Ecological Approach to Visual Perception","year":"1986","author":"gibson","key":"ref5"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01111"}],"event":{"name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","start":{"date-parts":[[2023,5,29]]},"location":"London, United Kingdom","end":{"date-parts":[[2023,6,2]]}},"container-title":["2023 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10160211\/10160212\/10161371.pdf?arnumber=10161371","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T13:36:12Z","timestamp":1690205772000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10161371\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,29]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/icra48891.2023.10161371","relation":{},"subject":[],"published":{"date-parts":[[2023,5,29]]}}}