Přístupnostní navigace
E-application
Search Search Close
Branch Details
Original title in Czech: Konstrukční a procesní inženýrstvíFSIAbbreviation: D-KPIAcad. year: 2018/2019Specialisation: Control of Machines and Processes
Programme: Machines and Equipment
Length of Study: 4 years
Accredited from: 1.1.1999Accredited until: 31.12.2020
Guarantor
prof. Ing. Václav Píštěk, DrSc.
Issued topics of Doctoral Study Program
A significant development in the area of mobile robotics was noticed in the last time in connection with the arrival of modern, powerful and mainly miniature computers and controllers. The development of mobile robotic devices is also correlative of to the development of sensory systems that are increasingly more accurate, faster and smaller. The role of mobile robots can be different. In some stores, Amazon, for example, a system of autonomous mobile robots is used. These mobile robots are able to bring and carry off cart with the desired goods which is needed. Furthermore, mobile robots are used for example for mapping indoor or outdoor space, such as service robots, or as a part of other mechanism, such as parking assistant in automobiles. The proposed project is focuses on mapping the interior and aims to design and implement algorithms of adaptive control of mobile robots. The project will design a system for obtaining data to create a 3D model of the mapped area. For designing the algorithm and for robot control the ROS framework will be used.
Tutor: Šťastný Jiří, prof. RNDr. Ing., CSc.
An increasing number of applications require the joint use of signal processing and machine learning techniques on time series and sensor data. Aim of the work will be data analytics, sensor processing software systems and sensor data fusion.
Tutor: Matoušek Radomil, prof. Ing., Ph.D.
The project contains the develop of a specialized platform for DNA sequence analysis with focus on large volumes of data that will include required algorithms for identification of structures like triplexes, quadruplexes and for protein motifs analyses with reporting and visualization tools and their storage in suitable database system. Proposed software will be implemented as a web service and will be available online for public usage. The software will be used for characterization and evaluation of the local DNA structures in DNA sequences with the focus to possibility to analyse whole genomes and different local DNA structures including triplexes and quadruplexes.
Bio-inspired robotic locomotion is a fairly new subcategory of bio-inspired design of robots. It is about learning concepts from nature and applying them to the design of real-world engineered systems. In addition to novel designs and methods for constructing robot morphologies, biology also inspires us to design improved software to enable robots to better interact with complex environments. The work will include simulation, path planning and control design of the bio-inspired robots.
Artificial intelligence methods belong among modern methods for optimization of process control. Using theese methods is especially suitable for problems which are very difficult to solve using classical mathematical methods or where using deterministic computation methods would require unacceptable simplification of the problem. An acquisition of the optimization data by means of modern methods and algorithms of artificial intelligence is a significant task in object classification. Approaches used by a graduant solving the aforementioned task are as follows: Analysis artificial intelligence methods, analysis algorithms for data classification and prediction.
There are three main types of bin picking: structured, semi-structured, and random bin picking. Each presents an increasing level of application complexity, cost and cycle time. We can say that random bin picking is already approaching mainstream of robotics. Random bin picking requires a convergence of technologies, particularly three main components that raise the robot’s intelligence: sensors, software, and end-of-arm tooling. Development in all three areas is moving us ever closer to that elusive prize.
Some dynamical systems exhibit a complex behavior known as deterministic chaos. The topic is focused on analysis and control of suitable chaotic models (with respect to a widest set of system's parameters) using computational intelligence.
As sensors spread across almost every industry, the internet of things is going to trigger a massive influx of big data. The work will focuse into where IoT will have the biggest impact and what it means for the future of big data analytics. Big Data Analytics is studying large datasets (big data) to identify hidden patterns, market trends, consumer preferences and other valuable information helping organizations to form strategic business decisions. Machine Learning is one of the tools used by data scientist, where a model is created that mathematically describes a certain process and its outcomes, then the model provides recommendations and monitors the results once those recommendations are implemented and uses the results to improve the model.
Virtual Reality (VR) is an established phenomenon. Enhanced Reality (augmented reality) is an indication used for real world images, supplemented by computer-generated objects. The aim of the work will be to analyze and recognize the image in real time, and to find, respectively. to interact with other contexts using artificial intelligence methods.
Study plan wasn't generated yet for this year.