Robustness Testing of Multi-Modal Models in Varied Home Environments for Assistive Robots

Fuente: arXiv
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Autori principali: Hirlimann, Lea, Zhang, Shengqiang, Schütze, Hinrich, Wicke, Philipp
Natura: Preprint
Pubblicazione: 2024
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author Hirlimann, Lea
Zhang, Shengqiang
Schütze, Hinrich
Wicke, Philipp
author_facet Hirlimann, Lea
Zhang, Shengqiang
Schütze, Hinrich
Wicke, Philipp
contents The development of assistive robotic agents to support household tasks is advancing, yet the underlying models often operate in virtual settings that do not reflect real-world complexity. For assistive care robots to be effective in diverse environments, their models must be robust and integrate multiple modalities. Consider a caretaker needing assistance in a dimly lit room or navigating around a newly installed glass door. Models relying solely on visual input might fail in low light, while those using depth information could avoid the door. This demonstrates the necessity for models that can process various sensory inputs. Our ongoing study evaluates state-of-the-art robotic models in the AI2Thor virtual environment. We introduce disturbances, such as dimmed lighting and mirrored walls, to assess their impact on modalities like movement or vision, and object recognition. Our goal is to gather input from the Geriatronics community to understand and model the challenges faced by practitioners.
format Preprint
id arxiv_https___arxiv_org_abs_2406_12443
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Robustness Testing of Multi-Modal Models in Varied Home Environments for Assistive Robots
Hirlimann, Lea
Zhang, Shengqiang
Schütze, Hinrich
Wicke, Philipp
Robotics
The development of assistive robotic agents to support household tasks is advancing, yet the underlying models often operate in virtual settings that do not reflect real-world complexity. For assistive care robots to be effective in diverse environments, their models must be robust and integrate multiple modalities. Consider a caretaker needing assistance in a dimly lit room or navigating around a newly installed glass door. Models relying solely on visual input might fail in low light, while those using depth information could avoid the door. This demonstrates the necessity for models that can process various sensory inputs. Our ongoing study evaluates state-of-the-art robotic models in the AI2Thor virtual environment. We introduce disturbances, such as dimmed lighting and mirrored walls, to assess their impact on modalities like movement or vision, and object recognition. Our goal is to gather input from the Geriatronics community to understand and model the challenges faced by practitioners.
title Robustness Testing of Multi-Modal Models in Varied Home Environments for Assistive Robots
topic Robotics
url https://arxiv.org/abs/2406.12443