6 citations · 10 across the 12 of their papers we have counts for
10 papers · 1 filter
ControlledShifts: Towards Standardizing Robustness Evaluation in Trajectory Prediction Under Distribution Shifts
Ingrid Navarro, Pablo Ortega-Kral, Yutong Duan +2
Trajectory prediction is central to safety in autonomous driving, yet learning-based predictors tend to degrade sharply when encountering scenarios poorly represented by their trai…
ScenarioCharacterization: A Modular Toolkit for Characterizing Safety across Trajectory Datasets
Ingrid Navarro, Yutong Duan, Jonathan Francis +1
We introduce ScenarioCharacterization, an open-source framework for automated, dataset-agnostic profiling of driving scenarios in trajectory datasets. Our framework is packaged as…
SEAL: Towards Safe Autonomous Driving via Skill-Enabled Adversary Learning for Closed-Loop Scenario Generation
Benjamin Stoler, Ingrid Navarro, Jonathan Francis +1
Verification and validation of autonomous driving (AD) systems and components is of increasing importance, as such technology increases in real-world prevalence. Safety-critical sc…
SoRTS: Learned Tree Search for Long Horizon Social Robot Navigation
Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas +4
The fast-growing demand for fully autonomous robots in shared spaces calls for the development of trustworthy agents that can safely and seamlessly navigate in crowded environments…
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…
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…
Learned Tree Search for Long-Horizon Social Robot Navigation in Shared Airspace
Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas +4
The fast-growing demand for fully autonomous aerial operations in shared spaces necessitates developing trustworthy agents that can safely and seamlessly navigate in crowded, dynam…
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…
Challenges in Close-Proximity Safe and Seamless Operation of Manned and Unmanned Aircraft in Shared Airspace
Jay Patrikar, Joao P. A. Dantas, Sourish Ghosh +11
We propose developing an integrated system to keep autonomous unmanned aircraft safely separated and behave as expected in conjunction with manned traffic. The main goal is to achi…
Social-PatteRNN: Socially-Aware Trajectory Prediction Guided by Motion Patterns
Ingrid Navarro, Jean Oh
As robots across domains start collaborating with humans in shared environments, algorithms that enable them to reason over human intent are important to achieve safe interplay. In…