Zobrazeno 1 - 10
of 1 550
pro vyhledávání: '"Ahmed, Nisar"'
When a robot autonomously performs a complex task, it frequently must balance competing objectives while maintaining safety. This becomes more difficult in uncertain environments with stochastic outcomes. Enhancing transparency in the robot's behavio
Externí odkaz:
http://arxiv.org/abs/2406.11984
Autor:
Acharya, Aastha, Lee, Caleb, D'Alonzo, Marissa, Shamwell, Jared, Ahmed, Nisar R., Russell, Rebecca
Deep learning offers promising new ways to accurately model aleatoric uncertainty in robotic estimation systems, particularly when the uncertainty distributions do not conform to traditional assumptions of being fixed and Gaussian. In this study, we
Externí odkaz:
http://arxiv.org/abs/2405.20513
Heterogeneous Bayesian decentralized data fusion captures the set of problems in which two robots must combine two probability density functions over non-equal, but overlapping sets of random variables. In the context of multi-robot dynamic systems,
Externí odkaz:
http://arxiv.org/abs/2401.16301
We consider the problem of evaluating dynamic consistency in discrete time probabilistic filters that approximate stochastic system state densities with Gaussian mixtures. Dynamic consistency means that the estimated probability distributions correct
Externí odkaz:
http://arxiv.org/abs/2312.17420
Autor:
Wakayama, Shohei, Ahmed, Nisar
For robotic decision-making under uncertainty, the balance between exploitation and exploration of available options must be carefully taken into account. In this study, we introduce a new variant of contextual multi-armed bandits called observation-
Externí odkaz:
http://arxiv.org/abs/2312.12583
This paper considers the problem of evaluating an autonomous system's competency in performing a task, particularly when working in dynamic and uncertain environments. The inherent opacity of machine learning models, from the perspective of the user,
Externí odkaz:
http://arxiv.org/abs/2312.09033
Current methods of deploying robots that operate in dynamic, uncertain environments, such as Uncrewed Aerial Systems in search \& rescue missions, require nearly continuous human supervision for vehicle guidance and operation. These methods do not co
Externí odkaz:
http://arxiv.org/abs/2309.06395
A key challenge in Bayesian decentralized data fusion is the `rumor propagation' or `double counting' phenomenon, where previously sent data circulates back to its sender. It is often addressed by approximate methods like covariance intersection (CI)
Externí odkaz:
http://arxiv.org/abs/2307.10594
Autor:
Khalid, Hassan, Ahmed, Nisar
BIQA (Blind Image Quality Assessment) is an important field of study that evaluates images automatically. Although significant progress has been made, blind image quality assessment remains a difficult task since images vary in content and distortion
Externí odkaz:
http://arxiv.org/abs/2307.09857
The nonlinear and stochastic relationship between noise covariance parameter values and state estimator performance makes optimal filter tuning a very challenging problem. Popular optimization-based tuning approaches can easily get trapped in local m
Externí odkaz:
http://arxiv.org/abs/2306.07225