JoVE Open Days on March 20

Library March 15, 2025

JoVE Open Days: Lunch & Learn Session

March 20 (Thursday) – We invite students, lecturers, researchers, and laboratory staff to join us for this special event:
JoVE Open Days (10:00 – 16:00) – JoVE specialist Catalina Dragoi will be available to provide consultations and answer any questions related to the JoVE video platform.
JoVE Lunch & Learn Session: Using JoVE for Research and Education (13:45) – A presentation on the features and possibilities of JoVE. All participants will be treated to tea, coffee, snacks, and pizza by JoVE.

Location: Plytinės g. 25, 1st floor lobby near P2-153

About JoVE:

JoVE (Journal of Visualized Experiments) is a university-subscribed video platform widely used and appreciated by students. It offers video recordings of laboratory experiments in physics, natural sciences, medicine, engineering, statistics, environmental sciences, and other fields. Each video is supplemented with textual information and journal articles. The journal content is carefully selected by editors and experts, and all JoVE articles are indexed in PubMed, Medline, Web of Science, Scopus, and other major databases. Lecturers can integrate all study-related materials into their Moodle courses.

Related news

New doctoral dissertation
New doctoral dissertation
VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Control of Robot Path Using an Artificial Intelligence System by Fusing Sensor Signal“ („Roboto trajektorijos valdymas dirbtinio intelekto sistema suliejant jutiklių signalus“) prepared at VILNIUS TECH by Vygantas Ušinskis. The dissertation was prepared in 2021–2026. Scientific consultant – Prof. Dr  Vytautas Bučinskas. The dissertation was defended at the public meeting of the Dissertation Defence Council of the Scientific Field of Mechanical Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 10 a.m. on 30 April 2026. The dissertation examines the problem of local robot navigation, where sensor data must be processed in real time to assess the environment and generate an adaptive motion trajectory. The research object is a local navigation system with sensor fusion for mobile robots operating in tunnels and confined channels. Navigation is divided into four parts: environment assessment, localisation, path planning, and motion execution. The analysis of localisation technologies enables the selection of an effective sensor set for obstacle detection. Heuristic and artificial intelligence methods allow generating an optimal trajectory that avoids collisions and maintains the goal. The work addresses navigation and obstacle detection in human-inaccessible environments using a cost-efficient combination of active and passive sensors, with experimental validation of the system’s performance. The dissertation consists of an introduction, three main chapters, conclusions, references, and a list of the author’s scientific publications on the topic of the dissertation. The introduction presents the problem, relevance, research objective and tasks, methodology, scientific novelty, practical significance, and defended statements, as well as the author’s publications and the structure of the dissertation. The First Chapter presents a literature review, including an overview and comparison of global and local path-planning methods, localisation technologies and their combinations, and sensor-fusion approaches used in mobile robots. Key factors affecting reliable navigation are identified, forming the basis for the dissertation tasks. The Second Chapter describes the developed research methodology for autonomous tunnel navigation: the operating principles of the red, green and blue (RGB) channel-camera- and laser-based optical obstacle detection system, sensor-fusion techniques, and the application of modified Vector Field Histogram (VFH) and machine-learning-based path-planning methods. The Third Chapter presents the research results: optical system experiments, path-planning simulations, a comparison between machine-learning and modified VFH methods, and the testing of the constructed robot prototype in a laboratory environment. Five research papers have been published on the topic of the dissertation: three in journals indexed in the Web of Science database, and two in conference proceedings. Additionally, five conference presentations related to the dissertation topic have been delivered in Lithuania and abroad. Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.  
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