The doctoral program in robotics provides advanced training and study in robotics-related topics consistent with the program focus on autonomy and AI, field robotics, human-robot interaction, smart materials, security, controls and estimation, bio-inspired systems and advanced manufacturing. The program prepares students for careers in local and national industry, government, national labs, academic research laboratories and university faculty positions.

The program provides a strong foundation in mathematics and engineering, while also allowing flexibility to select courses across departments to achieve the breadth and depth required for research advances beyond the state of the art. Students will achieve their educational goals through a combination of cross-disciplinary coursework and research under the supervision of one or more of the program’s faculty members.

For more information, see the Robotics website.

Required Courses and Credits

The PhD in Robotics offers a flexible curriculum that encourages in-depth study across disciplines from departments and programs hosted in the College of Engineering & Applied Science (CEAS), including aerospace engineering sciences, biomedical engineering, chemical and biological engineering, civil, environmental, and architectural engineering, computer science, electrical, computing, and energy engineering, engineering management, mechanical engineering, and the ATLAS Institute. To fulfill graduation requirements for the program, students must complete a minimum of 30 credit hours of coursework in courses numbered 5000 or above and taught by members of the graduate faculty, plus 30 hours of dissertation credit. More coursework may be required at the faculty advisor’s discretion. Coursework applying to the degree must be completed with grades of B- or better, and students must maintain a 3.00 GPA or higher while enrolled in the Graduate School. More detailed information and a list of approved courses can be found at the bottom of this page, under “Course Requirements.” 

A maximum of 21 credit hours of graduate coursework may be transferred from another accredited institution if the courses meet program and Graduate School standards.  All courses taken in a master's degree program at CU Boulder may be applied toward a doctoral degree at the university, provided that they are numbered 5000 or above and meet doctoral standards. For policies regarding good academic standing, please see the Academic Standards and Advising section of the university’s Graduate Catalog.

Preliminary Examination

Every student desiring to pursue the PhD degree must pass a preliminary examination. As a part of this evaluation, students must pass a multiple subject area oral examination to test fundamental robotics competency. Subject areas are based on the breadth bins within the robotics program and will be selected by the student. Overall performance in the required examinations will determine pass/fail status.

Comprehensive Examination

After passing the preliminary examination, students continue their coursework and prepare a written dissertation prospectus. When ready, they will take an oral comprehensive examination covering the graduate coursework and the dissertation prospectus. The oral examination is based primarily on a written proposal for the dissertation research provided by the student to committee members in advance. This examination is conducted before the student's doctoral committee of five or more graduate faculty members chosen by the student and approved by the program and the Graduate School.

PhD Dissertation

A minimum of 30 dissertation credit hours are required for the PhD degree. Up to 10 credit hours may be taken in any given semester. Students must write a dissertation based on original research conducted under the supervision of a graduate faculty member. The dissertation must fulfill all Graduate School requirements. After the dissertation is completed, an oral final examination on the dissertation and related topics is conducted by the student's doctoral committee of at least five members. The approved dissertation must be submitted to the program and the Graduate School.

Time Limit

Per Graduate School policy, all requirements for the program must be completed within six years of admission to the degree program. A waiver from the Graduate Committee is required for every semester beyond the time limit listed above. Students who wish to extend their time limit (up to one year) will also need to submit a petition to the Graduate School. 

Course Requirements

Students must complete ROBO 5000 Introduction to Robotics, plus one course selected from each breadth bin (as listed below), to complete their robotics fundamentals coursework requirements. These courses provide a foundation for advanced study in the field. PhD students must also complete two credit hours of ROBO 5009 Robotics Seminar and one credit hour of ROBO 5008 Introduction to Research as a requirement for graduation. The remaining 15 credit hours may be chosen from any of the courses on the approved ROBO courses list. This allows for maximum flexibility for students to tailor coursework for a variety of post-graduation career goals. Students may opt to replace up to six of those 15 credit hours with any course offered through a CEAS department or program as non-ROBO engineering electives. Any other course substitutions will require a petition to the Graduate Committee. Each PhD student, in consultation with their faculty advisor, is required to develop a course plan and submit it to the Graduate Committee for approval.

Core Course Requirement
ROBO 5000Introduction to Robotics3
Breadth Requirement: Dynamics and Mechatronics
Choose one:3
Space Flight Dynamics
Microavionics: Introduction to PIC Microcontrollers for Aerospace Systems
Embedding Sensors and Motors
Mechatronics and Robotics I
Finite Element Analysis
Bioinspired Robotics
Special Topics in Mechanical Engineering (Advanced Dynamics)
Advanced Robotics
Breadth Requirement: Perception and Control
Choose one:3
Statistical Estimation for Dynamical Systems
Linear Control Systems
Automatic Control Systems
Nonlinear Control Systems
Computer Vision
Control Systems Analysis
Applied Stochastic Signal Processing
Linear Control Systems
Nonlinear Control Systems
Special Topics in Mechanical Engineering (Advanced Computer Vision)
Breadth Requirement: Cognition and Interaction
Choose one:3
Algorithmic Motion Planning
Decision Making under Uncertainty
Convex Optimization and Its Applications
Advanced Robotics
Algorithmic Human-Robot Interaction
Machine Learning
Natural Language Processing
Theoretical Foundations of Autonomous Systems
Fundamentals of Neural Networks and Deep Learning
Current Topics in Computer Science (Deep Reinforcement Learning and Robotics)
Online Convex Optimization and Learning
Seminar Requirement
ROBO 5008Introduction to Research (Intro to Research)1
ROBO 5009Robotics Seminar 12
Robotics Electives 218
Small Uncrewed Aircraft System Guidance, Navigation, and Control
Advanced Spacecraft Dynamics and Control
Advanced State Estimation
Uncertainty Quantification
Special Topics (Hybrid Systems)
Special Topics (Verifiable Control of Stochastic Systems)
Special Topics (System Identification for Control)
Human Operation of Aerospace Vehicles
Nanomaterials
Introduction to Virtual Reality
Current Topics in Computer Science (Physical Human-Robot Interaction)
Real-Time Embedded Systems
Programmable Logic Embedded System Design
Special Topics (Game Theory)
Special Topics (Constrained Control)
Sampled Data and Digital Control Systems
Control Systems Laboratory
Control of Multi-agent Systems
Embedded Computer Vision
Machine Learning for Engineers
Modeling of Human Movement
Special Topics in Mechanical Engineering (Automated Mechanical Design)
Mechanics of Soft Matter
Micro-Electro-Mechanical Systems 1
Special Topics in Mechanical Engineering (Mechatronics 2)
Special Topics in Mechanical Engineering (Industrial Automation)
Special Topics in Mechanical Engineering (Robust Multivariable Control)

Learning Outcomes

By the completion of the program, students will be able to:

  • Core Knowledge in Robotics: Demonstrate an understanding of foundational robotics principles.
  • Broad Competency Across Robotics Domains: Demonstrate interdisciplinary knowledge in robotics, covering at least three core areas of study.
  • Technical Application Skills: Demonstrate capability to apply robotics tools and techniques in coursework to solve practical problems.
  • Depth of Knowledge in Specialization: Achieve expertise in a chosen area of robotics research.
  • Research Planning and Execution: Formulate and pursue original research questions, leading to independent investigation and problem-solving in robotics.
  • Research Communication: Clearly communicate research findings, both in writing and orally.