The Paul G. Allen School of Computer Science and Engineering Robotics Department is always looking for capable and hardworking undergraduates to join our cutting edge research. During the academic school year, almost all of our undergraduates earn research course credit that can be used as an elective credit.
Robotics researchers are engaged in ground-breaking work in mechanism design, sensors, computer vision, robot learning, Bayesian state estimation, control theory, numerical optimization, biomechanics, neural control of movement, computational neuroscience, brain-machine interfaces, natural language instruction, physics-based animation, mobile manipulation, and human-robot interaction. We are currently working to define large-scale joint initiatives that will enable us to leverage our multi-disciplinary expertise to attack the most challenging problems in field.
CSE Robotics is comprised of 5 different labs:
Take some time and review each lab above to read more about the research you would be most interested in. Once you have determined which lab you would like to join please fill out this form to the best of your ability and submit your application!APPLY HERE
Prospective researchers should have a strong programming background. We use Ubuntu and most of our code is either in Python or C++. They should be proficient with debugging code and comfortable with building large systems.
Depending on the specific project, we may also be looking for students with experience in machine learning (or a strong foundation in probability, linear algebra, and optimization), computer vision, embedded programming, electronics, mechanical design, or controls.
If you have a questions or concerns. Please contact Selest Nashef, Robotics Lab Manager at email@example.com.
Please note: We review applications on a weekly basis. If we believe a match is possible, we will contact you within 7 – 10 days to schedule an interview. You may re-apply every school year.
Below are a few prospective projects for incoming undergraduates, although we always welcome new ideas!
The Pixel Art project’s goal is to have a team of MuSHR cars collaboratively push boxes of various shapes and sizes into desired configurations, ideally creating an interesting structure/design. This project combines multi-agent navigation/planning, task allocation, and non-prehensile manipulation. This project is separated into three teams. The coordination team handles which cars get which boxes when. The navigation team addresses how each car will navigate without colliding with one another. The pushing team creates robust ways of pushing various boxes to desired configurations. Interested students should reach out, specifying which team they would like to join and why.
One million Americans cannot eat without assistance. This project aims to develop a robot-assisted feeding device that can help autonomously feed people with mobility impairments The project has several interesting research and engineering challenges, including: (1) bite acquisition (picking up food); (2) bite transfer (getting the food from the robot to the user’s mouth); (3) user-centered design and engineering (making it a comfortable and empowering experience for users). This project primarily involves coding in C++ and/or Python using the ROS framework (which you don’t have to know beforehand). It requires a commitment of at least 10 hr wk. Check out https://robotfeeding.io/ for more details, and share with us any ideas you’d be interested in working on to make the system better!
We are looking for a motivated undergraduate student who wants to learn more about open source software and robotics to help with maintaining and growing our software stack. Specifically, this entails engaging with our community to support issues, upgrading the stack to address issues, documentation, and testing. You will learn about various aspects of robotics, in addition to how an open source software team works. This is a great position for an student more interested in open source robotics and software engineering than pure robotics research.
We are developing algorithms for our chopsticks robot to pick up various items that may be challenging to grasp (slippery glass ball) or difficult to perceive (napkins). This project combines reinforcement learning, control, and imitation learning. The project currently involves Python, C++, and Julia. We’d expect a lot of coding, some paper reading, tweaking things in the simulator and testing things on the real robot.