State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...
A survivable agent system depends on the incorporation of many recovery features. However, the optimal use of these features requires the ability to assess the actual state of the...
Anthony R. Cassandra, Marian H. Nodine, Shilpa Bon...
— In this paper, we consider the standard state estimation problem over a congested packet-based network. The network is modeled as a queue with a single server processing the pa...
Michael Epstein, Abhishek Tiwari, Ling Shi, Richar...
We present a new method for carrying out state estimation in multiagent settings that are characterized by continuous or large discrete state spaces. State estimation in multiagen...
Abstract— Particle filters have been applied with great success to various state estimation problems in robotics. However, particle filters often require extensive parameter tw...
—Unmanned Air Vehicles (UAVs) have several advantages and disadvantages compared with Unmanned Ground Vehicles (UGVs). Both systems have different mobility and perception abiliti...
— In this note, an algebraic approach for state estimation of linear time-varying (LTV) systems is introduced. This approach is based on the following mathematical tools: Laplace...
This paper presents a sequential state estimation method with arbitrary probabilistic models expressing the system’s belief. Probabilistic models can be estimated by Maximum a po...
Abstract— Finite-range sensing and communication are factors in the connectivity of a dynamic mobile robot network. State estimation becomes a difficult problem when communicati...
Keith Yu Kit Leung, Timothy D. Barfoot, Hugh H. T....
A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System mo...