Curriculum Focus Areas

Applied Robotics Solutions

The Robotics Track is the only program at the University of Washington with guaranteed hands-on time with a variety of robotics platforms. It focuses on the practical deployment of robotics in real-world human-facing settings.

As robots are no longer used only in industrial settings but are moving into dynamic, human-occupied spaces with a variety of commercial platforms and applications, there is an increased demand for specialists who can program commercially available robots for a range of solutions.

Many of these skills are also highly transferable to other areas, including self-driving capabilities for cars and other vehicles or advanced unmanned systems (drones) deployment.

Key skills include:

• How robots sense the world around them: sensing, environment mapping, and navigation planning using computer vision and machine learning
• How robots can successfully communicate intent: human-robot interaction concepts and design
• How robots can pick up and move objects: detection and manipulation of objects (including complex non-rigid shapes)
• What environments are suitable for specific types of robots: Understanding infrastructure needs and limitations
• What are emerging service robotics applications: exploring a range of application areas including healthcare, food service, and logistics

IoT, Smart, and Applied AI solutions

The Connected Devices track allows students to explore a wide range of emerging hardware and software solutions.

Smaller and more advanced sensors and microcontrollers are paving the way for a wide range of new custom hardware devices, which can help users gather more data and process it more effectively with the assistance of AI/machine learning and cloud computing integration.

Students work together with a wide range of technology companies who provide expert insight and knowledge to develop technology solutions to real-world problems.

A wide range of technologies are explored in this track including:

• Augmented/virtual/mixed reality: Explore the latest application areas in a variety of fields
• Edge devices: Develop custom hardware and use a range of sensors to gather data with connectivity to other IoT devices.
• Unmanned systems (drones): Learn how unmanned systems are being utilized in a different applications, like forest mapping or monitoring whale health
• Cloud computing: Understand how data processing can be handled in the cloud, expanding the capability of a small hardware device to nearly infinite potential
• Computer vision: Explore how sensors can map the environment around them, detecting humans, animals, or a range of other objects visually.
• Machine learning: Apply the latest in AI and machine learning to analyze data and detect trends and issues using big data at scales that humans are unable to map.