We are looking for an ambitious PhD candidate who would like to develop novel methods for safe and socially compliant autonomous navigation in crowded urban canals, with a combination of machine learning (learning from historical data, reinforcement learning) and trajectory optimization approaches.

You will join a team of researchers within the context of the project "Sustainable Transportation and Logistics over Water: Electrification, Automation and Optimization (TRiLOGy)" funded by the Dutch Research Council (NWO). In this project, we will investigate (i) fleet management decisions at the high level (1 PhD position supervised by Assist. Prof. B. Atasoy) and (ii) autonomous navigation methodologies for autonomous vessels in urban canals (1 PhD position supervised by Assist. Prof. J. Alonso-Mora). You will be responsible for the latter, autonomous navigation.

The objective of the autonomous navigation part is to develop autonomy tools for navigation in inland waterways, among other manned and unmanned vessels. The main challenge to ensure safe and efficient navigation of autonomous vessels in urban waters is that of generating safe trajectories that (i) take into account the complex dynamics of the vessel, (ii) coordinate with other traffic participants and (iii) show socially-compliant behavior based on past experiece and historical data. In TRiLOGy we will rely on historical data from manned vessels and machine learning strategies (supervised learning, reinforcement learning, multi-agent reinforcement learning) to improve the performance of the motion planning system (trajectory optimization) and produce feasible human-like motions for the autonomous vessel. The developed motion planners will closely interact with the perception modules of the autonomous vessel. A typical scenario is that of crowded canals and intersections, where efficient navigation can be achieved with tight coordination among the interacting participants.

The autonomous navigation methods that will be developed in this project will be tested and verified through their application to autonomous vessels in the ResearchLab Autonomous Shipping (RAS). You will also interact with our industrial partners (Zoev City, Municipality of Amsterdam, Flying Fish and DEMCON Unmanned Systems), with the Amsterdam Institute of Advanced Metropolitan Solutions (AMS) and with MIT researchers working on the AMS Roboat project.

The PhD candidate will be embedded within the Autonomous Multi-robots Lab of the Department Cognitive Robocs at TU Delft. For more information of our ongoing research see https://www.autonomousrobots.nl.

Department
The main focus of the Cognitive Robotics department is the development of intelligent robots and vehicles that will advance mobility, productivity and quality of life. Our mission is to bring robotic solutions to human-inhabited environments, focusing on research in the areas of machine perception, motion planning and control, machine learning, automatic control and physical interaction of intelligent machines with humans. We combine fundamental research with work on physical demonstrators in areas such as self-driving vehicles, collaborative industrial robots, mobile manipulators and haptic interfaces. Strong collaborations exist with cross-faculty institutes TU Delft Robotics Institute and TU Delft Transport Institute), our national robotic ecosystem (RoboValley, Holland Robotics) and international industry and academia.

The candidate has a very good MSc degree in Robotics, Computer Science, Systems and Control, Electrical/Mechanical Engineering, Applied Mathematics, or a related field. The candidate must have strong analytical skills and must be able to work at the intersection of several research domains. Good programming skills and experience with Python/C++ and ROS are of foremost importance to implement the learning methods and the proposed designs on real ASVs. A very good command of the English language is required, as well as excellent communication skills. Candidates having exhibited their ability to perform research in machine learning, control, optimization, perception and/or robotics are especially encouraged to apply.

Fixed-term contract: 4 years.

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2325 per month in the first year to € 2972 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

Delft University of Technology

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation. For generations, our engineers have proven to be entrepreneurial problem-solvers both in business and in a social context. TU Delft offers 16 Bachelor’s and 32 Master’s programmes to more than 23,000 students. Our scientific staff consists of 3,500 staff members and 2,800 PhD candidates. Together we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact!

Faculty Mechanical, Maritime and Materials Engineering

The Faculty of 3mE carries out pioneering research, leading to new fundamental insights and challenging applications in the field of mechanical engineering. From large-scale energy storage, medical instruments, control technology and robotics to smart materials, nanoscale structures and autonomous ships. The foundations and results of this research are reflected in outstanding, contemporary education, inspiring students and PhD candidates to become socially engaged and responsible engineers and scientists. The faculty of 3mE is a dynamic and innovative faculty with an international scope and high-tech lab facilities. Research and education focus on the design, manufacture, application and modification of products, materials, processes and mechanical devices, contributing to the development and growth of a sustainable society, as well as prosperity and welfare.

Click here to go to the website of the Faculty of Mechanical, Maritime and Materials Engineering.