A Distributed Bayesian Data Fusion Algorithm with Uniform Consistency
Distributed Data Fusion (DDF) methods which possess guaranteed performance for ad-hoc
and arbitrarily connected networks empower more scalable, flexible and robust information …
and arbitrarily connected networks empower more scalable, flexible and robust information …
Bayesian stochastic gradient descent for stochastic optimization with streaming input data
We consider stochastic optimization under distributional uncertainty, where the unknown
distributional parameter is estimated from streaming data that arrive sequentially over time …
distributional parameter is estimated from streaming data that arrive sequentially over time …
Multistep dual control for exploration and exploitation in autonomous search with convergence guarantee
Inspired by the concept of recently proposed dual control for exploration and exploitation,
this article presents a multistep dual control for exploration and exploitation with guaranteed …
this article presents a multistep dual control for exploration and exploitation with guaranteed …
Dynamic event-triggered integrated task and motion planning for process-aware source seeking
The process-aware source seeking (PASS) problem in flow fields aims to find an informative
trajectory to reach an unknown source location while taking the energy consumption in the …
trajectory to reach an unknown source location while taking the energy consumption in the …
Multi-Source Encapsulation With Guaranteed Convergence Using Minimalist Robots
H Sinhmar, H Kress-Gazit - arXiv preprint arXiv:2404.19138, 2024 - arxiv.org
We present a decentralized control algorithm for a minimalist robotic swarm lacking memory,
explicit communication, or relative position information, to encapsulate multiple diffusive …
explicit communication, or relative position information, to encapsulate multiple diffusive …
Bayesian Network Structure Learning Algorithm Combining Improved Dragonfly optimization
D Ji, Z Sun - IEEE Access, 2023 - ieeexplore.ieee.org
Bayesian network structure learning is one of the current research hotspots in fields such as
statistics and machine learning. Although it has great potential and application prospects …
statistics and machine learning. Although it has great potential and application prospects …
BEINGS: Bayesian Embodied Image-goal Navigation with Gaussian Splatting
Image-goal navigation enables a robot to reach the location where a target image was
captured, using visual cues for guidance. However, current methods either rely heavily on …
captured, using visual cues for guidance. However, current methods either rely heavily on …
Cognition Difference-Based Dynamic Trust Network for Distributed Bayesian Data Fusion
Distributed Data Fusion (DDF), as a prevalent technique that empowers scalable, flexible,
and robust information fusing, has been employed in various multi-sensor networks …
and robust information fusing, has been employed in various multi-sensor networks …
Distributed Source Seeking Using A Bi-Level Distributed Model Predictive Control Algorithm
X Gao, Z Shu - 2023 62nd IEEE Conference on Decision and …, 2023 - ieeexplore.ieee.org
This paper presents a novel distributed source seeking algorithm, called Bi-Level Distributed
Model Predictive Control (BLMPC), to locate the source using a group of agents. During the …
Model Predictive Control (BLMPC), to locate the source using a group of agents. During the …
Risk-aware model predictive control enabled by bayesian learning
The performance of a model predictive controller depends on the accuracy of the objective
and prediction model of the system. Although significant efforts have been dedicated to …
and prediction model of the system. Although significant efforts have been dedicated to …