Our open and ongoing projects in this area are listed below, together with a selection of completed projects where relevant.

Fast map learning with mobile robots

Mobile robots often need to learn an initially uknown map of a position-dependent parameter from sampled values. Examples include learning radio transmission rates, the density of litter at each point, forest density, etc. Moreover, learning this map is often only one part of the robot's task -- the robot may also have a navigation objective, low energy consumption goals, etc. In this project, we aim to design and study a robot motion control strategy that optimally takes into account both map learning and the other objectives of the robot.

3D object recognition with mobile robots - PN3-Innovative-Cheques

The main aim of the project is the application of the techniques developed by the academic partner in the industrial environment from the beneficiary. The developed open-source modules are reusable and they can be adopted to the needs of the industrial beneficial. In order to close the perception-planning loop active perception techniques are proposed to be used also for the mapping application part. 

Active Perception for Flexible Object Handling in Smart Manufacturing

Intelligent object handling is becoming a must in a smart manufacturing system especially with the recent appearance of the motion compliant dual handed industrial robotic systems. Also the enhanced 3D sensing capabilities from the robotics domain enables us to reconsider our view about the smart manufacturing by enabling on the fly spatial perception of the robot working space.

Reinforcement learning and planning for nonlinear control applications

Planning methods for optimal control use a model of the system and the reward function to derive an optimal control strategy. Here we will consider in particular optimistic planning, a predictive approach that optimistically explores  possible action sequences from the current state. Due to generality in the dynamics and objective functions that it can address, it has a wide range of potential applications to problems in nonlinear control.

Assistive robot arms

Robots that assist elderly or disabled persons in their day-to-day tasks can lead to a huge improvement in quality of life. At ROCON we are pursuing assistive manipulators, as well as UAVs for monitoring at-risk persons. This project focuses on the first direction, and presents a wide range of opportunities for a team of students, starting from low-level control design and vision tasks, to high-level control using artificial intelligence tools. Each student will work on one well-defined subtopic in these areas. Specific tasks include:

Assistive autonomous UAVs

Robots that assist elderly or disabled persons in their day-to-day tasks can lead to a huge improvement in quality of life. This project employs UAVs to monitor at-risk persons, and research challenges range from real-time observation and observation to high-level vision and control for person monitoring. The project is appropriate for a team of students, each of them working on a well-defined subtask, such as:

AI based corridor racing

Ready for playing with an autonomous racing car? Join this project to learn AI related topics in the era of autonomous driving.

You should be interested/motivated in the fields:

  • Computer science
  • Image processing
  • Robotics

Mapping with mobile robots

The main aim of the project is to develop a robot being able to add semantic 3D information to an indoor map. The developed would be based on existing open-source modules in cooperation with Analog Devices.

Currently the company is producing a brand new 3 TOF depth camera. Within this project, the robot would be augmented with additional 3D sensors in order to facilitate the semantic mapping. 

Autonomous car prototype

Autonomous car is at the stage of becoming a mature commercial technology, attracting interest in a variety of industries. Accenture is partnering with UTCN to drive innovation in this field in Cluj-Napoca.


The main focus of the ROS2AR FTP is the integration of AR facilities into ROS-I by means of object recognition techniques in a production specific environment using smart glasses. The user is assisted in the object detection using landmark and 2D object detection in the HRI context. The detected object related information (e.g.

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