Title:
Towards Realistic Embodied AI Agents

dc.contributor.advisor Parikh, Devi
dc.contributor.author Datta, Samyak
dc.contributor.committeeMember Batra, Dhruv
dc.contributor.committeeMember Hoffman, Judy
dc.contributor.committeeMember Mottaghi, Roozbeh
dc.contributor.committeeMember Anderson, Peter
dc.contributor.department Computer Science
dc.date.accessioned 2022-08-25T13:35:21Z
dc.date.available 2022-08-25T13:35:21Z
dc.date.created 2022-08
dc.date.issued 2022-07-28
dc.date.submitted August 2022
dc.date.updated 2022-08-25T13:35:21Z
dc.description.abstract Recent years have witnessed the inception of a growing field of inquiry within the broader AI community termed as "Embodied AI". Problems studied under the umbrella of Embodied AI include the introduction of scene datasets and simulators to train AI agents to perform a wide spectrum of tasks requiring a curriculum of capabilities. While progress on this front has been commendable, it is nonetheless important and worthwhile to pause and carefully examine the real-world context under which such AI agents would be expected to operate. While doing so, it is critical to ensure "realism" i.e. the settings, parameters, and assumptions under which these agents and tasks are investigated in simulation indeed serve as the right test beds and high-fidelity precursors to the real world. Simulation has its own advantages of being fast, scalable/distributed, and safe and therefore, it is valuable to strive to make simulations more realistic. Towards that end, this thesis serves as an investigation into realism for Embodied AI agents in simulation. We study realism along 3 different axes. (1) Photorealism: The visual appearance of objects and rooms in indoor scenes, as viewed by the agent in simulation, must be a close approximation of what the agent would actually see in the real world. (2) Sensing and Actuation Realism: Embodied agents in simulation are often equipped with a variety of idealized sensors that provide highly privileged, noise-free sensing signals, depending on the task they are being trained for and take deterministic actions. This is in contrast to the dirty reality of noisy sensors and actuations in the real world. (3) Task Realism: Moving beyond realistic sensors and actuations, we need to ensure that the assumptions made while formulating tasks and the settings under which these tasks are being evaluated in simulation does indeed bode well with the deployment scenarios and use-cases in the real world. Finally, the thesis also explores connections between these different axes of realism.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/67245
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Embodied ai
dc.title Towards Realistic Embodied AI Agents
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Parikh, Devi
local.contributor.corporatename College of Computing
relation.isAdvisorOfPublication 2b8bc15b-448f-472b-8992-ca9862368cad
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
thesis.degree.level Doctoral
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