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Modern Robotics, Course 4:  Robot Motion Planning and Control
Coursera MOOC / Non-credit 0

Modern Robotics, Course 4: Robot Motion Planning and Control

About this course

Do you want to know how robots work? Are you interested in robotics as a career? Are you willing to invest the effort to learn fundamental mathematical modeling techniques that are used in all subfields of robotics? If so, then the "Modern Robotics: Mechanics, Planning, and Control" specialization may be for you. This specialization, consisting of six short courses, is serious preparation for serious students who hope to work in the field of robotics or to undertake advanced study. It is not a sampler. In Course 4 of the specialization, Robot Motion Planning and Control, you will learn key concepts of robot motion generation: planning a motion for a robot in the presence of obstacles, and real-time feedback control to track the planned motion. Chapter 10, Motion Planning, of the "Modern Robotics" textbook covers foundational material like C-space obstacles, graphs and trees, and graph search, as well as classical and modern motion planning techniques, such as grid-based motion planning, randomized sampling-based planners, and virtual potential fields. Chapter 11, Robot Control, covers motion control, force control, and hybrid motion-force control. This course follows the textbook "Modern Robotics: Mechanics, Planning, and Control" (Lynch and Park, Cambridge University Press 2017). You can purchase the book or use the free preprint pdf. You will build on a library of robotics software in the language of your choice (among Python, Mathematica, and MATLAB) and use the free cross-platform robot simulator V-REP, which allows you to work with state-of-the-art robots in the comfort of your own home and with zero financial investment.

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What you'll learn

  • understand key concepts of motion planning
  • implement feedback control systems
  • apply mathematical modeling techniques used in robotics
  • use a robot simulator to test planning algorithms

Course objectives

  • learn to plan robot motions in obstacle-rich environments
  • gain insights into motion control methods
Mechanical Engineering #feedback control #mathematical modeling #robotics #software tools #planning algorithms #motion planning #simulators #obstacle avoidance #c-space #graph search
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