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Postdoc Risk-aware Autonomous Navigation

Research / Academic
Delft

While automation offers opportunities to make society safer, it comes with new risks, some of which are fundamental and, others more technological. Autonomous agents require an understanding of how humans respond to the uncertainty and risk that they bring. From the agent’s perspective, actions are taken to bring itself into safety if there are uncertainties, but this may introduce new risks for others. For example, a vehicle that comes to a stand- still at a strange location, or reduces speed for a green traffic light, has already resulted in accidents, simply because this does not match human expectations. It is a major challenge to develop agents and frameworks that account for uncertainty, risk and interaction in the way humans do.
As human behavior depends on a tightly controlled perception-action cycle that carefully considers uncertainty and risk, so should the behavior of an autonomous agent. But this is not trivial to attain. For example, the dynamics of the environment in which it operates can be unpredictable, and control options may be unavailable or have limited ability. Inspired by how human brains deal with uncertainty, in this project you will develop probabilistic frameworks for motion planning in autonomous agents, such as cars or teams of drones. We will work on a fundamental understanding of how autonomous agents can cope with uncertainty and provide means for computing performance guarantees of autonomous AI agents under uncertainty, which will be integrated to various degrees into a use-case with self-driving shuttles.
Based on your experience and interests, you can focus on learning for planning, risk-aware motion planning under uncertainty, learning of interaction models, multi-robot learning, multi-modal prediction models, or other related topics to this project. You will work closely together with two PhD students, one focusing on motion planning and one focusing on trajectory prediction. You will also coordinate our efforts towards a demonstrator with a self-driving vehicle and interact with the consortium.
You will work on the NWO-NWA project "Acting under Uncertainty", which is formed by a consortium of several Dutch universities and companies, and be embedded within the Autonomous Multi-Robots Lab in the Department of Cognitive Robotics at TU Delft.
The goal of the Autonomous Multi-Robots Laboratory at the Delft University of Technology is to develop novel methods for navigation, motion planning, learning and control of autonomous mobile robots, with a special emphasis on multi-robot systems, on-demand transportation and robots that interact with other robots and humans in dynamic and uncertain environments. Building towards the smart cities of the future, our applications include self-driving vehicles, mobile manipulators, micro-aerial vehicles, last-mile logistics and ride-sharing. See: https://www.autonomousrobots.nl/
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. http://www.cor.tudelft.nl/

Requirements:

The candidate has, or is about to complete, a PhD degree in Robotics, Systems and Control, Computer Science, Applied Mathematics, or a related field. The candidate must be able to work at the intersection of several research domains and have a passion for doing ground-breaking theoretical research and applying it to real robots. Good programming skills and experience with programming languages such as Python and C++ are of foremost importance. Excellent command of the English language is required, as well as excellent communication skills. Candidates with a background in motion planning, control theory, machine learning or robotics are especially encouraged to apply. Experience with reinforcement learning algorithms is a strong plus.

Salary Benefits:

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: € 4.036 - € 5.090 per month gross). The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.
This position is a temporary assignment for 24 months.

Work Hours:

36 - 40 hours per week

Address:

Mekelweg 2