Deployment-Ready Robotics Skills
The MSTI Robotics track builds practical, hands-on skills focused on deploying real-world service robotics solutions.
Students work with commercial and open-source robotics platforms to design and implement systems that operate in real environments. The emphasis is not on building robots from scratch, but on integrating, adapting, and deploying existing platforms to solve applied problems.
Service Robotics is the fastest growing sector in the autonomous robotics industry
These systems assist humans by performing hazardous, repetitive, or cognitively demanding tasks. Designed to operate alongside people, service robots can navigate, manipulate objects, and adapt to dynamic environments with minimal human intervention.
The focus is on practical autonomy: robots that work reliably in real-world settings and deliver measurable value.
Skills You’ll Graduate With
MSTI Robotics students learn the skills necessary to develop and deploy autonomous service robotics solutions for real world needs and users.
- Learn to develop in ROS2
- Understand how to capture and process sensor data (including Computer Vision, LIDAR, etc.)
- Build environment maps and navigation with SLAM
- Set up data handling processes (distributed computing)
- Learn and apply machine learning/AI, including: Reinforcement Learning, Vision-Language-Action models
- Understand robotic manipulation and grasping
- Simulate robotic applications in multiple environments, including Nvidia IssacSim and IssacLab
- Orchestrate multiple robotics systems to complete a shared task
- UI and UX integration, including Human-Robot Interaction
- Ethical and responsible technology
Robotics Computing Requirements
In order to develop, simulate, and deploy robotics solutions, student must have specific computer hardware. Some UW computing resources are available, but to gain the most out of the program, please refer to the minimum and recommended requirements below.
- Students must have contemporary, Intel or AMD-based computers. Apple computers and Snapdragon powered computers cannot effectively run the development software used in the course.
- Laptops are recommended, but home desktops that meet the requirements can also be used.
Important
Some advanced computing equipment is available in our labs, but we do not have enough equipment for dedicated individual use.
The minimum requirements will allow you to complete assignments, but may be slower or limit advanced simulation.
- Intel Core i7 (7700/7th Generation) or AMD Ryzen 5 (4000/Zen 3) or better
- 32GB RAM
- 256 GB SSD
- Discrete Graphics Card with 8GB of VRAM (Nvidia RTX recommended)
- Windows 11 or Ubuntu 22.04/24.04 (Preferred)
The recommended system will allow you to perform advanced simulation and system development faster and more efficiently.
- Intel Core i7 (9th generation) or AMD Ryzen 7 5000 series or better
- 64GB RAM
- 500GB NVMe/PCIe 4.0 SSD
- Nvidia RTX 4080 or better with 16GB of VRAM
- Nvidia RTX highly recommended (GeForce or PRO)
- 16GB or more of VRAM recommended to smoothly run reinforcement learning and simulations
- Windows 11 or Ubuntu 22.04/24.04 (Preferred)
Robotics Track Journey
Core Knowledge
Learn robotics fundamentals through core MSTI coursework like sensors and circuits, the prototyping process, machine learning and signal/data processing. Use interdisciplinary courses to undertake user research, develop a user interface, and build a business foundation.
Robotics Labs
Learn basic robotics structure and systems through mobile robot systems. Sense the enivronment and learn how to build autonomous navigation plans from an environment map. Use robot manipulators (arms) to detect and grasp objects.
Robotics Projects
Develop an integrated robotics solution using commercial and open-source robots, and begin considering how to create a product that meets user needs and has a well-thought out business case.
Robotics Capstone
Develop a functional robotics solution using open source or commercial robots, some of which may be supplied by industry partners. Demonstrate the value of your robotics solution with real users and use that data to refine your solution.
Robotics Alumni Stories
Practical Robots: Aayush Kumar Creates Robots with Real-World Uses
Aayush Kumar is advancing what’s possible with his quadruped robot project. His work combines hardware innovation, software optimization, and a vision for practical applications.
Aayush Kumar is advancing what’s possible with his quadruped robot project. His work combines hardware innovation, software optimization, and a vision for practical applications.