activity
20202024
most citedURA*: Uncertainty-aware Path Planning using Image-based Aerial-to-Ground Traversability Estimation for Off-road Environments

2 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2024

A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics

Ivan A. Fernandez, Subash Neupane, Trisha Chakraborty +5

Industry 4.0 has witnessed the rise of complex robots fueled by the integration of Artificial Intelligence/Machine Learning (AI/ML) and Digital Twin (DT) technologies. While these…

cs.RO2023★ 2 cited

Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities

Subash Neupane, Shaswata Mitra, Ivan A. Fernandez +5

Robotics and Artificial Intelligence (AI) have been inextricably intertwined since their inception. Today, AI-Robotics systems have become an integral part of our daily lives, from…

cs.RO2023★ 2 cited

URA*: Uncertainty-aware Path Planning using Image-based Aerial-to-Ground Traversability Estimation for Off-road Environments

Charles Moore, Shaswata Mitra, Nisha Pillai +4

A major challenge with off-road autonomous navigation is the lack of maps or road markings that can be used to plan a path for autonomous robots. Classical path planning methods mo…

cs.CL2021

Neural Variational Learning for Grounded Language Acquisition

Nisha Pillai, Cynthia Matuszek, Francis Ferraro

We propose a learning system in which language is grounded in visual percepts without specific pre-defined categories of terms. We present a unified generative method to acquire a…

cs.RO2020

Sampling Approach Matters: Active Learning for Robotic Language Acquisition

Nisha Pillai, Edward Raff, Francis Ferraro +1

Ordering the selection of training data using active learning can lead to improvements in learning efficiently from smaller corpora. We present an exploration of active learning ap…