Title:
Foundation Models for Robotics
Foundation Models for Robotics
dc.contributor.author | Garg, Animesh | |
dc.date.accessioned | 2024-01-29T18:42:13Z | |
dc.date.available | 2024-01-29T18:42:13Z | |
dc.date.issued | 2023-11-29 | |
dc.description | Presented on November 29, 2023 at 2:30 p.m. as a part of the IRIM Robotics Days for Industry 2023. | |
dc.description | Animesh Garg is a Stephen Fleming Early Career Assistant Professor at School of Interactive Computing at Georgia Tech. He leads the People, AI, and Robotics (PAIR) research group. He is on the core faculty in the Robotics and Machine Learning programs. Garg's research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments. His group focuses on understanding structured inductive biases and causality on a quest for general-purpose embodied intelligence that learns from imprecise information and achieves flexibility & efficiency of human reasoning. | |
dc.description | Runtime: 18:24 minutes | |
dc.format.extent | 18:24 minutes | |
dc.identifier.uri | https://hdl.handle.net/1853/73259 | |
dc.language.iso | en | |
dc.publisher | Georgia Institute of Technology | |
dc.rights | Unless otherwise noted, all materials are protected under U.S. Copyright Law and all rights are reserved | |
dc.rights.metadata | https://creativecommons.org/publicdomain/zero/1.0/ | |
dc.rights.uri | https://rightsstatements.org/page/InC/1.0/?language=en | |
dc.subject | Foundation models | |
dc.subject | LLMs | |
dc.subject | Manipulation | |
dc.subject | Robot learning | |
dc.title | Foundation Models for Robotics | |
dc.type | Mixed Material | |
dc.type.genre | Lecture | |
dspace.entity.type | Publication | |
local.contributor.corporatename | College of Computing | |
local.contributor.corporatename | School of Interactive Computing | |
local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
local.relation.ispartofseries | Robotics Days for Industry | |
relation.isOrgUnitOfPublication | c8892b3c-8db6-4b7b-a33a-1b67f7db2021 | |
relation.isOrgUnitOfPublication | aac3f010-e629-4d08-8276-81143eeaf5cc | |
relation.isOrgUnitOfPublication | 66259949-abfd-45c2-9dcc-5a6f2c013bcf | |
relation.isSeriesOfPublication | c2b2768b-9924-42a6-b0f1-fa6403fd47a1 |
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