18 citations · 126 across the 28 of their papers we have counts for
12 papers · 1 filter
REMM: Revisable Embodied Memory for Manipulation
Revanth Krishna Senthilkumaran, Ruwan Wickramarachchi, Alessandro Oltramari +1
Long-horizon manipulation requires robots to retain task-relevant history while revising conclusions no longer supported by physical evidence. Retaining observations alone does not…
SafeShift: Safety-Informed Distribution Shifts for Robust Trajectory Prediction in Autonomous Driving
Benjamin Stoler, Ingrid Navarro, Meghdeep Jana +3
As autonomous driving technology matures, safety and robustness of its key components, including trajectory prediction, is vital. Though real-world datasets, such as Waymo Open Mot…
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…
What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery
Peide Huang, Xilun Zhang, Ziang Cao +6
Training control policies in simulation is more appealing than on real robots directly, as it allows for exploring diverse states in an efficient manner. Yet, robot simulators inev…
Core Challenges in Embodied Vision-Language Planning
Jonathan Francis, Nariaki Kitamura, Felix Labelle +3
Recent advances in the areas of Multimodal Machine Learning and Artificial Intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision…
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…
Distribution-aware Goal Prediction and Conformant Model-based Planning for Safe Autonomous Driving
Jonathan Francis, Bingqing Chen, Weiran Yao +2
The feasibility of collecting a large amount of expert demonstrations has inspired growing research interests in learning-to-drive settings, where models learn by imitating the dri…
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…
Learn-to-Race Challenge 2022: Benchmarking Safe Learning and Cross-domain Generalisation in Autonomous Racing
Jonathan Francis, Bingqing Chen, Siddha Ganju +10
We present the results of our autonomous racing virtual challenge, based on the newly-released Learn-to-Race (L2R) simulation framework, which seeks to encourage interdisciplinary…
Safe Autonomous Racing via Approximate Reachability on Ego-vision
Bingqing Chen, Jonathan Francis, Jean Oh +2
Racing demands each vehicle to drive at its physical limits, when any safety infraction could lead to catastrophic failure. In this work, we study the problem of safe reinforcement…
Learn-to-Race: A Multimodal Control Environment for Autonomous Racing
James Herman, Jonathan Francis, Siddha Ganju +7
Existing research on autonomous driving primarily focuses on urban driving, which is insufficient for characterising the complex driving behaviour underlying high-speed racing. At…