EEC255 – Robotic Systems

3 units – Winter Quarter; alternate years

Lecture: 3 hours

Prerequisite: None

Grading: Letter; homework, class projects and exams as determined by instructor.

Catalog Description:

Introduction to robotic systems. Mechanical manipulators, Kinematics, manipulator positioning and path planning. Dynamics of manipulators. Robot motion programming and control algorithm design.

Expanded Course Description:

  1. Introduction to Robotics
    1. Definition of robotics
    2. Role of robotics in automation and manufacturing
    3. Classification of robot manipulators and robotic systems
  2. Robot Arm Kinematics
    1. Rigid motions and homogeneous transformation
    2. Forward kinematics and Denavit-Hartenberg representation
    3. Inverse kinematics
    4. Algebraic method
    5. Geometric method
  3. Motion Kinematics
    1. Jacobian
    2. Singularities
    3. Inverse velocity and acceleration problems
    4. Numerical method for inverse kinematics solution
  4. Manipulator Dynamics
    1. Lagrange-Euler formulation
    2. Kinematic and potential energy
    3. Equations of motion
    4. Moving coordinate system
    5. Newton-Euler formulation
  5. Trajectory Planning
    1. Polynomial paths and cubic segments
    2. Linear segments with parabolic blends
    3. Coordinated Cartesian space motion planning
  6. Robot Manipulator Control
    1. Review of PID control methods and disturbance rejection
    2. Actuator dynamics and independent joint control
    3. Computed torque method for robot manipulator joint space control
    4. Cartesian space control problems


  1. Robotics: Control Sensing, Vision, and Intelligence, K. S. Fu, R. C. Gonzales, and C. S. G. Lee, McGraw-Hill, 1987.

Engineering Design Statement:

Much of this course is devoted to the analysis, modeling, and design of mechanical manipulator kinematics, dynamics, and motion control. Because of the fact that manipulator models are highly nonlinear and complex, model selection, analysis techniques and assumptions made are very important aspects of the design process. Students are shown how to recognize certain factors and assess their impact on computational feasibility and system performance during the design process. The course includes individual projects which require computer simulations and laboratory experimentation to verify the validity of the designs.

ABET Category Content:

Engineering Science: 1 credit
Engineering Design: 2 credits

Instructor: Gundes


Last revised: February 2006