Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP220102398
Funding Status
Active
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Funded Activity Summary
Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently learn complex interaction and navigation behaviours that transfer to unseen environments. Our research should benefit new applications in domains of economic and societal importance that are currently too complex, unsafe, and uncertain for robot assistants, such as aged care, advanced manufacturing and domestic robotics.Funded Activity Details
Start Date: 10-2022
End Date: 09-2025
Funding Scheme: Discovery Projects
Funding Amount: $515,000.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Adaptive Agents and Intelligent Robotics | Computer Vision | Artificial Intelligence and Image Processing
ANZSRC Socio-Economic Objective (SEO)
Expanding Knowledge in the Information and Computing Sciences |
