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The Robotics Concentration
  • The Department of Computer Science at RPI offers an MS degree with specialization in Robotics.
  • Details about the program requirements can be found below.

The main goal of Robotics
  • To create intelligent machines that are beneficial to society

Why specialize in Robotics (other than to help society)?
  • Unique combination of fundamental knowledge and cutting-edge technology
  • Excellent preparation for Phd studies
  • Increase your range of job opportunities

The main intellectual challenge of Robotics
  • Understanding how to design and control robots to perform a wide range of useful tasks alone, in groups, or in collaboration with humans, and to do so in ways that are socially acceptable.

Useful background for Robotics research
  • The field of Robotics is so broad, that students with many different backgrounds can contribute to the field.
  • Assuming knowledge of the subject matter in the courses Robotic I and Robotics II, the subjects most useful in pursuing the goals of the CS Robotics Lab are (in no particular order): algorithms, scientific computing, software engineering, optimization and math programming, Bayesian filtering, multibody dynamics, machine learning, database systems, control theory, and signal processing.

  • For information regarding admissions, please follow this link.
  • For general inquiries about admissions and the program, please follow this link.

Degree Requirements
Students must complete a plan of study that includes 30 credits at the 4000 and 6000 levels. At least 18 of these credits must be at the 6000 level. There are five required courses. In addition, students must take three Robotics electives.

Required Courses:
  • CSCI-6140: Computer Operating Systems
  • CSCI-6050: Computability and Complexity
  • CSCI-6990: Master's Research (six credits)
  • CSCI-4490/ECSE-4490: Robotics I
  • CSCI-6491/ECSE-6491: Robotics II

Robotics Electives:

Three courses from the following:

Advanced Robotics/Intelligent Systems:
  • CSCI-6100: Machine and Computational Learning
  • CSCI-4150: Intro. to Artificial Intelligence
  • ECSE-6410: Robotics and Automation Systems
  • ECSE-4963: Mechatronics
  • MANE-6420: Multibody Systems

Perception and Interaction:
  • CSCI-6974: Mathematical Techniques for Computer Vision, Graphics and Robotics
  • CSCI-6963: Advanced Computer Graphics
  • CSCI-6270: Computational Vision
  • ECSE-6995: Distributed Systems and Sensors
  • ECSE-6610: Pattern Recognition

  • ECSE-6440: Optimal Control Theory
  • ECSE-6240: Nonlinear Control Systems
  • ECSE-6460: Multivariable Control Systems
  • ECSE-6480: Adaptive Systems
  • ECSE-4440: Control Systems Engineering

Mathematical Foundations:
  • CSCI-6210: Design and Analysis of Algorithms
  • CSCI-4260: Graph Theory
  • CSCI-4800: Numerical Computing
  • CSCI-4820: Intro. to Numerical Methods for Differential Equations
  • ECSE-6790: Computational Geometry
  • ECSE-4500: Probability for Engineering Applications
  • ECSE-4510: Discrete Time Systems
  • ECSE-6430: Optimization Methods
  • DSES-6961: Optimization Algorithms and Applications

Note: additional robotics electives may be approved by the Robotics Program Committee.
Topic revision: r6 - 05 Aug 2010, trink@LAB.CS.RPI.EDU
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