Projects

The IDM research group has more that 20 year of history during which was collaboration of many research and application projects.

Currently solved projects

• "COMP4DRONES -Leveraging CPS Composability & Modularity for Customized and Autonomous Civilian Drones"

  Objectives:	The aim of the Comp4Drones project is to provide key technologies enabler framework to safe integration of certified drones into the airspace. In particular, COMP4DRONE will leverage composability and modularity for customizable and trusted autonomous drones for civilian services. The project will take into account recent developments in the regulation in this area from the European Aviation Safety Agency (EASA) and, by extension, the Joint Authorities for Rulemaking on Unmanned Systems (JARUS).
  Participants:	Faculty of Applied Sciences (University of West Bohemia in Pilsen)
  Funded by:	C4D - H2020
  Duration:	2020-2022
  Contact:	Ing. Miroslav Flídr, Ph.D.

• Fundamental research project "Tensor Decomposition in Active Fault Diagnosis for Stochastic Large Scale Systems" for the Czech Science Foundation (GAČR)

  Objectives:	The project deals with the development of active fault diagnosis (AFD) algorithms for stochastic discrete-time large-scale systems. To achieve the feasibility of the algorithms, tensor decompositions (TDs) will be employed in several components of the AFD algorithm design. In particular, the TDs will be applied for the dynamic programming responsible for the active aspect of the diagnosis, for the nonlinear Bayesian state estimation responsible for the learning, and for the information fusion responsible for merging the information learned by individual AFD nodes. To meet the requirements involved, novel TD algorithms will be developed with a special focus on non-negative variants, variants with limited sensitivity, and functional TD. Combining the components fused with the developed TDs in the decentralized, distributed or hierarchical AFD architectures exploiting structural properties of the large-scale system will lead to feasible algorithms capable of coping with the complexity of nonlinear stochastic large-scale systems.
  Participants:	Faculty of Applied Sciences (University of West Bohemia in Pilsen)
  Funded by:	GACR GA 22-11101S
  Duration:	2022-2024
  Contact:	doc. Ing. Ondřej Straka, Ph.D.

• Fundamental research project "Intelligent distributed Estimation Architectures" for the Czech Science Foundation (GAČR)

  Objectives:	The project deals with development of the state estimation methods for nonlinear discrete-time stochastic dynamic systems. In particular, the stress is laid on distributed state estimation methods, where the system state is estimated simultaneously by a set of local processors (LPs). Each LP processes just a sub-set of all available measurements, which is determined by a physical layout of the sensors and communication throughput. Subsequently, particular local estimates are fused by the global fusor. The main goal of the project is to develop a conceptually new concept of synthesis of the distributed state estimator, which is based on the active and intelligent adaptation of the topology and structure of the LPs, fulfilling the global estimation aim. Both the global decision maker and LPs will be treated. The global decision-maker provides, besides the global state estimate fulfilling the estimation aim, also instructions affecting the topology and structure of the LPs. The LPs are designed to provide the output with properties and quality specified by the global decision-maker.
  Participants:	Faculty of Applied Sciences (University of West Bohemia in Pilsen)
  Funded by:	GAČR, GA20-06054J
  Duration:	2020-2022
  Contact:	doc. Ing. Jinřich Duník, Ph.D.

• Fundamental research project "Anticipative Point-Mass Method for High-Performance Estimation and Navigation (APHEN)" for Office of Naval Research

  Objectives:	The objective of the project is to theoretically advance multi-dimensional non-linear, non-Gaussian (NL/NG) estimation methods, which represent a key component of any modern system for target tracking, navigation, and positioning. NL/NG estimation is a significant research topic towards enhanced performance of equipment in stand-off, cluttered, and denied environments. The Anticipative Point-Mass Method for High-Performance Estimation and Navigation (APHEN) project will focus on the development of the point-mass method (PMM) which, due to current advances of parallel computer processing units, has become an attractive signal processing algorithm offering high performance and reliable estimates. The PMM has been applied in many areas among which the terrain-aided navigation (TAN) is a widely known one. The TAN allows continuous navigation even in GPS-denied environments, i.e., in the environment, where the GPS signal is intentionally (e.g., because of spoofing or jamming) or unintentionally (e.g., because of geomagnetic storms or multipath) interfered.
  Participants:	Faculty of Applied Sciences (University of West Bohemia in Pilsen)
  Funded by:	Office of Naval Research
  Duration:	2020-2022
  Contact:	doc. Ing. Jinřich Duník, Ph.D.

Past projects