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Students.

Meet

Arthur Helsloot

Using a robot to rearrange objects on a table is a relatively easy task to solve, since the top view of the environment allows the robot to see all objects it has to deal with.

Jasper Wijkhuizen

One of the main challenges for mobile robots in semi-structured and possibly cluttered environments like supermarkets is to optimize the navigation quality, which for this research is about the safety and performance trade-off.

Stefan Bonhof

Imagine this: you are walking through the cereal aisle of your local supermarket, when you see a pack of ice-cream slowly thawing into a small pool of sadness. You don’t want to see that, right?

Shreyash Palande

Robots perform flawless demos in the controlled environment under human supervision but tend to fail in real world especially when deployed for long period. With increasing complexity, a greater number of components are added to the system thereby increasing the probability of it being faulty.

Evelien Heerkens

For robots to increase the efficiency in stores, it is important that they can navigate autonomously in a store environment, in which changes occur on top of the previously known environment.

Paul van Houtum

Sensor technologies have triggered my interest during my time studying at the TU Delft. Being able to perform my master’s thesis research in this field, while using an actual robot at AIRLab is great! The research lies in the scope of classifying objects towards their function (affordance), rather than their type, using perception sensors.

Mohammed Mâachou

Mobile manipulators are becoming more applicable in dynamic environments. Algorithms for task planning and execution for autonomous robots are needed to be more adaptive, reactive and fault tolerant against unforeseen contingencies.

Anne van der Star

Since I’ve made a cucumber picking robot in my minor robotics, I have a special interest in working with robotics and biological products. Therefore, I have been working at the TU Delft AgTech Institute during my study en joined AIRLab for my thesis project.

Zixuan Wan

My project is about Bayesian neural networks that use posterior distributions for weights instead of precise numbers, so that uncertainty can be reflected in the prediction process. At the same time, model compression and architecture search can be employed due to the information of posterior distribution.

Anna Mészáros

My goal is to make teaching robots how to perform interaction tasks more intuitive and safe. The particular focus of my work is on multi-modal interaction tasks in which both a force interaction as well as a position control have to be executed. In order to achieve this, I employ learning from demonstration coupled with further machine learning techniques.

Stavya Bhatia

I am working on a dynamic and stochastic vehicle routing problem that focuses on routing a fleet of vehicles in the last-mile delivery for retail. In particular, such problems deal with many complexities and require decisions to be made based on incomplete information. My goal would be to improve assignment + routing performance by eliminating the adverse effects of incomplete information using suitable anticipatory techniques.

Koen Bakker

The important part of having a robot in a retail environment is not so much that it has to work perfectly. The important part is that people actually feel comfortable having the robot around. The goal of my research is to create a path planning algorithm that adapts to the environment, with emphasis on the people in the environment. I believe that with a combination of self-adaptation and machine learning you can create a robot that mimics socially acceptable retail store behaviour.

Ahmed Bakay

In order to use robots for stocking the shelves, it’s important to know what the robot sees and how the robot interprets the things it sees. One of the relevant things a robot sees in a supermarket is the products. We (humans) can very quickly determine what product we see based on multiple characteristics (material, text, colour, size, environment, etc.). A robot cannot do that out of itself, it needs algorithms to determine which product it sees, this branch of computer vision is called “object recognition”.