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MTS-804 Motion Planning for Mobile Robots
Campus College of E&ME
Programs PG
Session Spring Semester 2017
Course Title Motion Planning for Mobile Robots
Course Code MTS-804
Credit Hours 3-0
Pre-Requisutes Introduction to Robotics, Matlab
Course Objectives
  • This course is designed to serve as an introduction the broad area of robotics, intelligent machines that can act of their work, and specifically mobile robotics.
  • It will deal primarily with algorithmic issues.
  • It will discuss how we can approach the three key issues in mobile robotics: building a map of our surroundings, knowing where we are, and formulating a plan to get us where we want to go (mapping, localization and path planning)?
Detail Content
  • An overview of concepts in robot motion planning.
  • Sensor-Based Motion Planning Algorithms
    • the “Bug” algorithms
    • the TangentBug algorithm
    • Implementation
  • The configuration space of a rigid body.
  • The classical motion planning paradigms:
    • the potential functions
    • the roadmaps
    • the cellular decompositions
  • The sampling based algorithms:
    • the probabilistic roadmaps
    • single query sampling based planners
  • Map making and SLAM
    • the Kalman filter
    • the SLAM problem
    • the Bayesian approaches to map making
  • Non-holonomic drive systems
    • the types of drive systems
    • the legged robots
    • the crawling robots
    • trajectory planning for non-holonomic systems
  • Motion planning for multiple robots
    • Notion of configuration x time space
    • Mapping of moving obstacles in configuration x time space
    • Centralized vs. decoupled planning
    • Decoupled planning techniques: Velocity tuning, coordination diagram, prioritized planning
Text/Ref Books
  • Principles of Robot Motion, Theory Algorithms and Implementations by Howie Choset, Kevin Lynch, Seth Hutchinson, George Kantor Wolfram Burgard, Lydia Kavraki, and Sebastian Thrun
  • Probabilistic Robotics Sebastian Thrun
  • Any Other book on Mobile Robots
Time Schedule Spring Semester 2017
Faculty/Resource Person Dr. Kunwar Faraz Ahmed Khan
PhD. (Mechanical Engineering), University of Toronto, Canada
Discipline: Mechatronics
Specialization: Mechanical Engineering