Contact

Contact address:

Jan Faigl
Office: KN:E-333a
Karlovo namesti 13
121 35 Prague 2, Czechia
Phone.: +420-2-2435 7400
E-mail: faiglj@fel.cvut.cz

 

Administrative address:

Dept. of Computer Science
Artificial Intelligence Center (AIC)
Faculty of Electrical Engineering (FEE)
Czech Technical University in Prague (CTU)
Technická 2, 166 27 Prague 6
Czechia

 

Directions and Maps of Charles Square Campus of CTU

Finding the CTU campus at Karlovo namesti 13 (charles Square) is easy. Karlovo namesti is a large rectangular park. Travel by metro (line B) to station Karlovo namesti. There are two exits from this station. Take the exit closer to the city center, labelled Karlovo namesti. (The second exit leads to Palackeho namesti; when you appear less than 100 meters from Vltava river then you are on the wrong side).

The entrance to the campus is in a yellowish Renaissance Revival building from 1860 on the corner of Karlovo namesti and Resslova street. You will appear in the underpass after leaving the metro area. One of the underpass exits leads to the corner of the CTU building. The direction is roughly diagonally left from metro exit. If there is a bakery shop on your right hand side in the underpass then it is the correct exit. Climb up the stairs and you will see the entrance to CTU directly in front of you.

 

Directions from the airport

  • Bus No. 119 to the stop Nádraží Veleslavín (final stop)
  • Underground (Metro) line A to Mustek (6th stop)
  • Change to the line B and go to the station Karlovo namesti (2nd stop)

or

  • Bus No. 100 to the stop Zlicin (final stop)
  • Underground (Metro) line B to station Karlovo namesti (10th stop)

Directions from the Main station (Hlavni nadrazi)

  • Underground (Metro) line C to Florenc (1st stop)
  • Change to line B and go to station Karlovo namesti (4th stop)

Directions from the Holesovice station (Holesovicke nadrazi)

  • Underground (Metro) line C to Florenc (2nd stop)
  • Change to line B and go to station Karlovo namesti (4th stop)

Open Positions


If you are interested in working within the Computational Robotics Lab,  please read the following carefully.

Most of the positions are for CTU, FEE students in the form of internships, final thesis theme, semestral projects, and occasionally with working agreement depending on the research and related project. Those who are interested in collaboration with us and are from abroad, please attached your CV, transcripts, and a draft of your expected research ideas that fit our research topics.

 

Positions for CTU, FEE Students

There are several specific positions, but it is also possible to specify the topic later. The general topics of our interests are mostly related to

  • Locomotion control of multi-legged robotics
  • Asymptotically optimal or near-optimal motion planning for complex robotic systems
  • Multi-goal trajectory planning for aerial vehicles
  • Autonomous navigation of unmanned ground vehicles
  • Unsupervised learning in multi-goal planning and cost traversal assessment
  • Online and incremental learning from data streams
  • Multi-robot and multi-agent collaborative planning using distributed and decentralized approaches

Specific Positions of the Current Needs

Scientific Programmer / Research Assistant
Topic Implementing algorithms for mission planning with single and a team of aerial vehicles – soft computing techniques
Suitable for Student(s) who likes planning (TSP-like problems), UAV, and AI techniques applied in robotics problems
Requirements C++/Julia or willingness to learn

Positions
 

Scientific Programmer / Research Assistant
Topic Parallel and massively parallel computational resources in unsupervised learning and real-time decision making approaches motivated by multi-robot persistent monitoring scenarions
Suitable for Student(s) who likes parallel computational resources such as GPU or FPGA or multi-core processing deployed in the solution of the robotic mission planning problems
Requirements C++/Julia, CUDA/OpenCL or willingness to learn

 

Scientific Programmer / Developer – Low-power communications
Topic Design and development of low-power communication modules for local communication among a team of small mobile robots autonomously building wireless communication infrastructure
Suitable for Student(s) with interest in communication devices (aka IoT), communication protocols, and distributed/decentralized control
Requirements Passion or willingness to learn new technologies

 

Scientific Programmer / Developer – FPGA
Topic FPGA computational resources in supporting online-decision making in robotic applications motivated by persistent environment monitoring.
Suitable for Student(s) with the passion to exploiting capabilities of FPGA to speed algorithms by several order of magnitude while keeping the power requirements very low – targeting to deployments in mission-critical systems such robotics and space deployments
Requirements Familiarity with FPGA and their programming using high-level synthesis (HLS) tools

 

Scientific Programmer / Research Assistant
Topic Combinatorial optimizations combined with continous optimization motivated by mission planning for unmanned robotic vehicles such as UAV and UGV
Suitable for Student(s) who likes to touch cutting-edge approaches in multi-goal missions planning
Requirements Combinatorial optimization, Integer or Mixed-Integer Linear Programming (ILP and MILP), experience or willingness to learn CPLEX or Gurobi, C++/Julia or eventually Python or Matlab

 

Developer
Topic Become familiar with CRL (Comrob) codebase. Improve the organization and documentation of the source codes.
Suitable for Students who like to become familar with C++ and software development in AI in robotics tasks
Requirements C++ or willingness to learn

 

Scientific Programmer / Research Assistant
Topic Reliable localization of UGV platforms using sensor fusion techniques and state-of-the-art implementations of Simultaneous Localization and Mapping (SLAM) algorithms
Suitable for Student(s) with interest in machine vision and sensor fusion
Requirements C++, ROS or willingness to learn