Syllabus: Introduction to Robotics


Instructor: Ryan Meuth (

This course is Co-Listed as Computer Engineering 300 and Electrical Engineering 300.  
Course Number:
   Computer Engineering - 73120
   Electrical Engineering - 73119
    Programming Course of some kind (CS 153 level recommended)
    Stat 215/217


Robotics is an inherently interdisciplinary engineering field, encompassing electrical, computer and mechanical engineering, as well as computer science, mathematics, physics, systems engineering, and in some instances psychology and cognitive neuroscience.  The breadth of the problems presented by robotics development encourages the integration of knowledge and problem solving methods from a wide range of fields.  With the advent of autonomous vehicles in the military and consumer robotics products, such as the iRobot Roomba, the robotics industry is growing rapidly, and is expected to continue to do so as consumer spending on robotics increases.  Study of the discipline of robotics can give engineers a valuable perspective on systems integration, as well as experience in a wide range of fields and real-world problem solving, increasing the flexibility of the engineer in a rapidly changing world. 

This course will introduce students to technologies behind robotics projects ranging from the historical to the state of the art, as well as fundamentals on robotics architectures, sensing, navigation, and control.  Topics covered will include basic sensor and image processing, sensor fusion, world modeling, planning, kinematics, control, software agents, machine learning and simulation.  Instruction will utilize example problems presented by real-world competitions such as the Intelligent Ground Vehicle Competition (IGVC), AHS First Responder, and Association for Unmanned Vehicle Systems International (AUVSI) Unmanned Aerial Vehicle (UAV), and Unmanned Underwater Vehicle (UUV) competitions.   

Students enrolled in the course will construct and program a small mobile robot from a kit, which they will learn to program to move, react to sensor states, perform simple tasks, and ultimately interact with other class robots.

 In addition to choosing their own projects, students will have the option to select semester projects that can be incorporated into MS&T's robotics competition entries such as the IEEE Robotics Competition and Intelligent Ground Vehicle Competition.  

Course Goals: 

  • Introduce students to methods used in robotics and autonomous vehicles, including:
    • Sensing:
      • Sensor Processing
      • Image Processing (including Stereo-vision)
      • Sensor Fusion
      • Pose Estimation
    • Planning:
      • World-Models
        • Maps
        • Rules
      • Behavior-Based Architectures
        • Reactive
        • Subsumption
      • Path Planning
      • Navigation Algorithms
    • Acting:
      • Kinematics
        • Wheeled Robot (2D Kinematics)
        • Arm (3D Kinematics)
        • Fixed Wing Aircraft
        • Rotary Aircraft
      • Motor Control
    • Software Agents
    • Machine Learning
    • Simulation Environments
  • Improve student's presentation skills
  • Give students experience with robotics research projects


  • 6 Bi-weekly Projects (intended to be implemented in Matlab)
  • 1 Semester Project including
    • Presentation (25%)
    • Paper (75%)
  • At least one 30 min presentation to the class on a research topic