Intelligent Transport Lab
Center for Cognitive Modeling MIPT
Center for Cognitive Modeling MIPT
About Lab
The Intelligent Transport Laboratory was created in 2019 at the Moscow Institute of Physics and Technology (MIPT) on the initiative of the Scientific and Design Bureau of Computer Systems (NKB VS). Together with the Laboratory of Cognitive Dynamic Systems, it is part of the Center for Cognitive Modeling MIPT.
The laboratory specializes in the design and creation of embedded integrated electronic control systems for various types of transport (including unmanned vehicles) and intelligent image processing and synthesis systems using deep machine learning methods, Big Data technologies, virtual and augmented reality, autonomous navigation and mapping (SLAM) methods. ) and etc.
The laboratory specializes in the design and creation of embedded integrated electronic control systems for various types of transport (including unmanned vehicles) and intelligent image processing and synthesis systems using deep machine learning methods, Big Data technologies, virtual and augmented reality, autonomous navigation and mapping (SLAM) methods. ) and etc.
Dmitry Yudin
Head of the Intelligent Transport Lab MIPT - NKB VS
candidate of technical sciences,
Associate Professor, Department of System Research, MIPT,
Senior Researcher, Laboratory of Cognitive Dynamical Systems
Research interests:
Technical vision
Artificial Intelligence
Deep learning
Robotics
Profile
Associate Professor, Department of System Research, MIPT,
Senior Researcher, Laboratory of Cognitive Dynamical Systems
Research interests:
Technical vision
Artificial Intelligence
Deep learning
Robotics
Profile
Main research topics
associated with the development of mathematical and software for intelligent transport systems:
associated with the development of mathematical and software for intelligent transport systems:
- Onboard multimodal vision systems;
- Mapping and navigation systems;
- Autonomous traffic control systems;
- Geographic Information Systems;
- Human-machine control interfaces;
- Virtual computer simulation for training and evaluation of perception, navigation and control algorithms;
- Integrated on-board information and control systems.
Applied tools
Software development is carried out using Python and C++ programming languages, NVidia Cuda and TensorRT libraries, ROS1/2 robots operating system, Docker.
Many projects are related to integration into embedded systems, in particular with the use of NVidia Jetson Orin, Xavier, TX2 and Nano.
PyTorch are used as basic software platforms for researching deep learning algorithms.
Software development is carried out using Python and C++ programming languages, NVidia Cuda and TensorRT libraries, ROS1/2 robots operating system, Docker.
Many projects are related to integration into embedded systems, in particular with the use of NVidia Jetson Orin, Xavier, TX2 and Nano.
PyTorch are used as basic software platforms for researching deep learning algorithms.
Research and development directions
Partners
Some Activities
Contacts
Email: yudin.da@mipt.ru
141701, Moscow region,
Dolgoprudny, Institutskiy per., 9.
141701, Moscow region,
Dolgoprudny, Institutskiy per., 9.