Location Uncertainty

Location uncertainty, the imprecise knowledge of an object's position, is a critical challenge across diverse fields, from robotics and space exploration to image processing and audio signal processing. Current research focuses on developing robust algorithms and models, such as hierarchical POMDPs for robotic manipulation, diffusion models for predicting satellite collision probabilities, and stochastic positional embeddings for image recognition, to effectively manage and mitigate the impact of this uncertainty. These advancements are crucial for improving the reliability and efficiency of autonomous systems, enhancing safety in space operations, and advancing the capabilities of machine learning models. The ultimate goal is to create systems that can operate effectively despite inherent positional ambiguity.

Papers

September 27, 2024

A POMDP-based hierarchical planning framework for manipulation under pose uncertainty
Muhammad Suhail Saleem, Rishi Veerapaneni, Maxim Likhachev
Strategic Manipulation Observable Markov Decision Process Hierarchical Planning Closed Loop Planning Pose UnceRtainty Location Uncertainty Anytime Algorithm

November 15, 2023

Probability of Collision of satellites and space debris for short-term encounters: Rederivation and fast-to-compute upper and lower bounds
Ricardo Ferreira, Cláudia Soares, Marta Guimarães
Collision Avoidance Lower Bound Collision Scenario Multiple Satellite Space Debris Location Uncertainty

November 9, 2023

Predicting the Position Uncertainty at the Time of Closest Approach with Diffusion Models
Marta Guimarães, Cláudia Soares, Chiara Manfletti
Diffusion Model Time Matter Location Uncertainty Closest Point Orbit Determination

July 31, 2023

Stochastic positional embeddings improve masked image modeling
Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun
Image Modeling Masked Image Modeling Deep Linear Location Uncertainty Stochastic Positional Embeddings

February 27, 2023

3D Neural Beamforming for Multi-channel Speech Separation Against Location Uncertainty
Rongzhi Gu, Shi-Xiong Zhang, Dong Yu
Source Separation Neural Beamformer Location Uncertainty

March 9, 2022

Multi-Agent Active Search using Detection and Location Uncertainty
Arundhati Banerjee, Ramina Ghods, Jeff Schneider
Data Detection Target Detection Detection of Uncertainty in Exceedance Active Search Multi Agent Active Search Location Uncertainty

Location Uncertainty

Papers

A POMDP-based hierarchical planning framework for manipulation under pose uncertainty

Probability of Collision of satellites and space debris for short-term encounters: Rederivation and fast-to-compute upper and lower bounds

Predicting the Position Uncertainty at the Time of Closest Approach with Diffusion Models

Stochastic positional embeddings improve masked image modeling

3D Neural Beamforming for Multi-channel Speech Separation Against Location Uncertainty

Multi-Agent Active Search using Detection and Location Uncertainty