13 citations · 20 across the 5 of their papers we have counts for
5 papers · 1 filter
MOSAIC: Learning Unified Multi-Sensory Object Property Representations for Robot Learning via Interactive Perception
Gyan Tatiya, Jonathan Francis, Ho-Hsiang Wu +2
A holistic understanding of object properties across diverse sensory modalities (e.g., visual, audio, and haptic) is essential for tasks ranging from object categorization to compl…
Cross-Tool and Cross-Behavior Perceptual Knowledge Transfer for Grounded Object Recognition
Gyan Tatiya, Jonathan Francis, Jivko Sinapov
Humans learn about objects via interaction and using multiple perceptions, such as vision, sound, and touch. While vision can provide information about an object's appearance, non-…
Knowledge-driven Scene Priors for Semantic Audio-Visual Embodied Navigation
Gyan Tatiya, Jonathan Francis, Luca Bondi +4
Generalisation to unseen contexts remains a challenge for embodied navigation agents. In the context of semantic audio-visual navigation (SAVi) tasks, the notion of generalisation…
Transferring Implicit Knowledge of Non-Visual Object Properties Across Heterogeneous Robot Morphologies
Gyan Tatiya, Jonathan Francis, Jivko Sinapov
Humans leverage multiple sensor modalities when interacting with objects and discovering their intrinsic properties. Using the visual modality alone is insufficient for deriving in…
ACuTE: Automatic Curriculum Transfer from Simple to Complex Environments
Yash Shukla, Christopher Thierauf, Ramtin Hosseini +2
Despite recent advances in Reinforcement Learning (RL), many problems, especially real-world tasks, remain prohibitively expensive to learn. To address this issue, several lines of…