4 papers
Belief-Conditioned One-Step Diffusion: Real-Time Trajectory Planning with Just-Enough Sensing
Gokul Puthumanaillam, Aditya Penumarti, Manav Vora +5
Robots equipped with rich sensor suites can localize reliably in partially-observable environments, but powering every sensor continuously is wasteful and often infeasible. Belief-…
Uncertainty-Aware Guidance for Target Tracking subject to Intermittent Measurements using Motion Model Learning
Andres Pulido, Kyle Volle, Kristy Waters +3
This paper presents a novel guidance law for target tracking applications where the target motion model is unknown and sensor measurements are intermittent due to unknown environme…
Global Uncertainty-Aware Planning for Magnetic Anomaly-Based Navigation
Aditya Penumarti, Jane Shin
Navigating and localizing in partially observable, stochastic environments with magnetic anomalies presents significant challenges, especially when balancing the accuracy of state…
Real-time Uncertainty-Aware Motion Planning for Magnetic-based Navigation
Aditya Penumarti, Kristy Waters, Humberto Ramos +2
Localization in GPS-denied environments is critical for autonomous systems, and traditional methods like SLAM have limitations in generalizability across diverse environments. Magn…