Thesis supervisor: András László Majdik
Location of studies (in Hungarian): Department of Material Handling and Logistics Systems Abbreviation of location of studies: ALRT
Description of the research topic:
This Ph.D. studentship will investigate one (or more) of the following research areas: cooperative aerial-ground 3D machine perception and environment modeling, appearance-based localization in GPS denied environments, multisensory and semantic simultaneous localization and mapping (SLAM), spatial artificial intelligence for long-term autonomy, agile vision-based navigation and machine learning for autonomous logistics systems. The goal of this project is to extend the current state-of-the-art by creating new concepts and algorithms to enable new applications in aerial logistics.
Tasks related to the fellowship include:
• explore new research ideas, design novel algorithms, and perform experiments
• develop customized solutions for autonomous ground and flying platforms
• write code to be used as a ROS node on real-world systems
• collaborate and interact with a multidisciplinary and ambitious team
The candidate must have excellent mathematical, algorithm design and coding skills (C++/Python, ROS). The research fellowship offers the opportunity to be part of an ambitious team, work with state-of-the-art robot sensors, hardware and software, and benefit from excellent support to produce and disseminate research contributions in the leading international conferences and journals.
Required language skills: English Further requirements: High level C / C ++ and / or python programming knowledge is required. Computer vision knowledge and experience in ROS is an advantage.
Number of students who can be accepted: 2
Deadline for application: 2022-12-19
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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