Research Areas

Four Focus Areas

Focus courses must belong to the same focus area, which is selected by the student among four possible choices. At most 1 focus course can be at the undergraduate level, from the approved list in each focus area.

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Artificial Intelligence and Perception

Students will learn about recent advancements in machine learning, computer vision, and data mining, all of which enable robots to perceive and reason about their environment. Students can choose from the following courses.

Courses

ME 202: Spectral Computational Methods
ME 233: Artificial Intelligence for Design
EE 142: Pattern Recognition and Analysis of Sensor Data
EE 146: Computer Vision
EE 236: State and Parameter Estimation Theory
EE 241: Advanced Digital Image Processing
EE 243: Advanced Computer Vision
EE 244: Computational Learning
EE 245: Robotic Sensing and Navigation
EE 247: Current Topics in Computer Vision and Pattern Recognition
CS 170: Introduction to Artificial Intelligence
CS 171: Introduction to Machine Learning and Data Mining
CS 173: Natural Language Processing
CS 205: Artificial Intelligence
CS 227: Probabilistic Models for Artificial Intelligence
CS 229/EE 240: Machine Learning/Pattern Recognition
CS 235: Data Mining Techniques

Control and Navigation

Students will learn about the design of algorithms to control a robot based on sensory data, and how to efficiently plan the trajectories of a robot to navigate an environment. Students can choose from the following courses.

Courses

ME 121: Feedback Control
ME 145: Robotic Planning and Kinematic
ME 220: Optimal Control and Estimation
ME 221: Kinematics and Dynamics of Robots
ME 223: Secure and Reliable Control Systems
EE 132: Automatic Control
EE 144: Introduction to Robotics
EE 151: Introduction to Digital Control
EE 231: Convex Optimization in Engineering Applications
EE 236: State and Parameter Estimation Theory
EE 237: Nonlinear Systems and Control
EE 238: Linear Multivariable Control
EE 239: Optimal Control
EE 245: Robot Sensing and Navigation
EE 246: Intelligent Transportation Systems

Embedded Platforms and System Design

Students will learn about the design of embedded platforms for real-time decision making in perception, reasoning, navigation and control. Students can choose from the following courses.

Courses

EE 217: GPU Architecture and Parallel Programming
EE 246: Intelligent Transportation Systems
EE 255: Real-Time Embedded Systems
EE 258: Modeling and Synthesis of Cyber-Physical Systems
CS 171: Introduction to Machine Learning and Data Mining
CS 256: Modeling and Synthesis of Cyber-Physical Systems

Mechanical Design and Fabrication

Students will learn about the design of rigid and flexible robots to perform specialized tasks for a variety of applications, including agriculture, medicine, and monitoring. Students can choose from the following courses.

Courses

ME 174: Machine Design
ME 175B: Mechanical Engineering Design
ME 175C: Mechanical Engineering Design
ME 210: Sustainable Product Design
ME 230: Computer-Aided Engineering Design
ME 232: Computational Design Tools
ME 233: Artificial Intelligence for Design
ME 271: Nanoscale Science and Engineering

Robotics @ UCR

Research Areas

Four Focus Areas

Artificial Intelligence and Perception

Courses

Control and Navigation

Courses

Embedded Platforms and System Design

Courses

Mechanical Design and Fabrication

Courses

Bourns College of Engineering