Copy the page URI to the clipboard
Chiatti, Agnese; Bardaro, Gianluca; Matteucci, Matteo and Motta, Enrico
(2023).
URL: https://aaai.org/Conferences/AAAI-23/
Abstract
Robots can help with many visually-intense and onerous tasks that are traditionally carried out by human workers, such as the inspection of critical infrastructures or the management of crops. However, before we can safely delegate tasks to robots, we ought to ensure that they can reliably make sense of the environments in which they are deployed. To this aim, building world models that resemble the complexity of the real world is critical. Despite research efforts in the AI and Robotics communities towards tackling the problem of model building, few works exist that approach this problem by considering perspectives and lessons learned from both fields. In this position paper, we use three strategic application domains in Robotics to argue for the centrality of visual model building to support robot sensemaking.
Viewing alternatives
- Request a copy from the author This file is not available for public download
Item Actions
Export
About
- Item ORO ID
- 86506
- Item Type
- Conference or Workshop Item
- Project Funding Details
-
Funded Project Name Project ID Funding Body GATEKEEPER 857223 European Union Horizon 2020 L'Oreal-UNESCO Italy "For Women in Science" program Not Set L'Oreal-UNESCO Fondation - Keywords
- service robotics; field robotics; visual intelligence; computer vision; semantic mapping; object anchoring
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Intelligent Systems and Data Science
- Copyright Holders
- © 2022 Agnese Chiatti, © 2022 Gianluca Bardaro, © 2022 Matteucci Matteo, © 2022 Motta Enrico
- Depositing User
- Agnese Chiatti