Doctor of Philosophy with a Major in Robotics

Program website:

Program requirements:

Students pursuing a PhD in Robotics must take 36 credit hours of core research and elective courses, pass a comprehensive qualifying exam with written and oral components, and successfully complete, document, and defend a piece of original research culminating in a doctoral thesis. Students select a home school, such as ECE, AE, ME, or IC, and apply for admission to the PhD program in robotics through that home school.

All PhD programs must incorporate a standard set of Requirements for the Doctoral Degree.

Program of Study

The main emphasis of the Ph.D. program is the successful completion of an original and independent research thesis. The degree requirements are designed around this goal.

Minimum Requirements

  • Completion of 33 semester hours of courses with a letter grade
  • Passing a comprehensive qualifying exam with written and oral components.
  • Successfully conducting, documenting, and defending a piece of original research culminating in a doctoral thesis.
  • Note: A maximum of two classes (6 semester hours) at the 4000-level may be used to satisfy 33 semester hour requirement.
  • Minor Field of Study
CS/AE/ECE/ME 7785Introduction to Robotics Research3
CS/AE/ECE/ME 8750Robotics Research Foundation I3
CS/AE/ECE/ME 8751Robotics Research Foundation II3
Foundation Courses 19
Elective Courses 29
Courses Outside of the Major6
Total Credit Hours33
Ph.D. Candidacy

Prior to completing all of these requirements, Georgia Tech defines the Ph.D Candidate milestones. Admission to candidacy requires that the student:

  1. Complete all course requirements (except the minor);
  2. Achieve a satisfactory scholastic record;
  3. Pass the comprehensive examination;
  4. Submit and receive approval naming the dissertation topic and delineating the research topic.
Core Area Courses

The following courses are in the robotics core areas of Mechanics, Control, Perception, Artificial Intelligence, and Human-Robot Interaction (HRI). They are used to select three foundation courses and three targeted elective courses. Foundation courses are noted with a footnote.

AE 6211Advanced Dynamics II3
AE 6230Structural Dynamics3
AE 6270Applied Nonlinear Dynamics3
AE 6520Advanced Flight Dynamics3
BMED 8813Special Topics (Robotics) 13
CS 7496Computer Animation3
ME 6405Introduction to Mechatronics3
ME 6407Robotics 13
ME 6441Dynamics of Mechanical Systems3
ME 6442Vibration of Mechanical Systems3
ME 7442Vibration of Continuous Systems3
AE 6505Random Processes and Kalman Filtering3
AE 6506Aerospace Guidance and Navigation3
AE 6511Optimal Guidance and Control3
AE 6530Multivariable Linear Systems and Control 13
AE 6531Aerospace Robust Control I3
AE 6532Aerospace Robust Control II3
AE 6534Control of Aerospace Structures3
AE 6580Aerospace Nonlinear Control3
AE 8803Special Topics (Nonlinear Stochastic Optimal Control)3
ECE 6550Linear Systems and Controls 13
ECE 6551Digital Control3
ECE 6552Nonlinear Systems and Control3
ECE 6553Optimal Control and Optimization3
ECE 6554Adaptive Control3
ECE 6555Optimal Estimation3
ECE 6559Advanced Linear Systems3
ECE 6563Networked Control and Multiagent Systems3
ME 6401Linear Control Systems 13
ME 6402Nonlinear Control Systems3
ME 6403Digital Control Systems3
ME 6404Advanced Control System Design and Implementation3
CS 6476Introduction to Computer Vision GR 13
CS 7476Advanced Computer Vision3
CS 7616Pattern Recognition3
CS 7636Computational Perception3
CS 74993D Reconstruction and Mapping in Computer Vision, Robotics, and Augmented Reality3
CS 7626Introduction to Behavioral Imaging3
CS 7643Deep Learning3
ECE 6255Digital Processing of Speech Signals3
ECE 6258Digital Image Processing3
ECE 6273Methods of Pattern Recognition with Application to Voice3
ECE 6560Partial Differential Equations in Image Processing and Computer Vision3
ME 6406Machine Vision 13
Artificial Intelligence
CS 3600Introduction to Artificial Intelligence3
CS 6601Artificial Intelligence 13
CS 7612Artificial Intelligence Planning3
CS 7640Learning in Autonomous Agents3
CS 7643Deep Learning3
CS 7648Interactive Robot Learning3
CS 8803Special Topics (Mobile Manipulation)3
CS 8803Special Topics (Robot Intelligence)3
CS 8803Special Topics (Robot Motion Planning)3
CS 8803Special Topics (Computation and the Brain)3
CS 8803Special Topics (Statistical Techniques in Robotics)3
CS/ECE 8803Special Topics (Probabilistic Graph Models and ML in High Dimensions)3
ECE 6254Statistical Machine Learning3
Human-Robot Interaction (HRI) 2
AE 6721Evaluation of Human Integrated Systems 13
CS 7633Human-Robot Interaction 13
CS 6455User Interface Design and Evaluation3
CS 6750Human-Computer Interaction3
CS 7648Interactive Robot Learning 13
CS 8803Special Topics (Computational Social Robotics)3
ISYE 6215Models in Human-Machine Systems3
ISYE 6224Topics in Human-Integrated Systems3
PSYC 6011Cognitive Psychology3
PSYC 6014Sensation and Perception3
PSYC 6017Human Abilities3
PSYC 7101Engineering Psychology I: Methods3
PSYC 7104Psychomotor and Cognitive Skill Learning and Performance3

Foundation course


HRI includes two core courses. Students are encouraged, but not required to take both HRI core courses. Students taking both core courses may use their second core class in place of an HRI elective course.

Minor Field of Study

The Robotics Ph.D. Minor consists of two related courses (six semester credit hours) outside of robotics that forms a coherent field of study in accordance with the Institute’s policies. The minor courses must be distinct from any of the robotics core areas (i.e., are not listed under any of the 5 core areas on this website) but can be taken from the student’s home school as long as they are distinct from robotics courses (e.g., ECE-ROBO student can take ECE circuits courses or ME students can take fluid mechanics courses).