MSc

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

Bosch future mobility challenge

The Bosch Future Mobility Challenge is an event organized by Robert Bosch Romania, targeted to engage students in a technical oriented competition and offer them a professional context to prove their talent. The competition offers students the opportunity to prove their abilities and to overcome challenges in a team. It is of great interest to us to support this commitment and to promote upcoming engineers. We are convinced that young talent, with fresh ideas and extraordinary commitment, is enormously important for the future of mobility.

Connected Industrial Worker

The main aim of this project would be to use the advanced AR/VR capabilities of the Hololens and the Google Tango devices to help an industrial worker in his everyday tasks. This project is part of the on-going research with the Accenture company using the Baxter cobot.

3D semantic mapping

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 the Braintronix company.

Currently the company is producing the VIPER mobile platorm for research and development purposes. Within this project, the robot would be augmented with additional 3D sensors in order to facilitate the semantic mapping. 

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.

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:

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:

Sliding mode control of inverted pendulum

This project will develop sliding mode controllers and observers for the Quanser rotational inverted pendulum. The control objective is to stabilize the inverted pendulum at the upward position from a single swing up. The control system should ensure robustness properties in respect with parametric uncertainties, measurement noise, external disturbance, small time delays. Preliminary results will be validated in simulations, after which real-time implementation and validation will be performed.

Observation and control for a power-assisted wheelchair

This project takes place in the context of a collaboration with the University of Valenciennes, France, involving Professors Thierry-Marie Guerra and Jimmy Lauber, Sami Mohammad at Autonomad Mobility, and PhD student Guoxi Feng. The overall objective is to control the power supplied by the electrical motor of the wheelchair, so as to push (or brake) together with the user without taking over entirely. This ensures that the user can achieve their driving task but still keeps them active. Specific tasks, each of which could be handled by a student, include:

Optimal control of a communicating robot

Mobile robots typically communicate wirelessly, both to receive commands and to provide sensing data. The range of communication is finite and bandwidth varies with the distance from the base station (wireless antenna), so communication quality is strongly affected by the trajectory of the robot. However, trajectory control design rarely takes this into account. In this project, we aim to design a control strategy that optimally takes into account both the navigation and communication needs of the robot.

AI planning and learning 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 recent 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.

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