Autonomous Navigation for Flying Robots

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  • 8 Sequences
  • Introductive Level
  • Starts on May 4, 2015
  • Ends on June 29, 2015

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Course details

Syllabus

After successful participation of this module, students will be able to

  • Understand the flight principles of quadrotors and their application potential
  • Specify the pose of objects in 3D space and to perform calculations between them (e.g., compute the relative motion)
  • Explain the principles of Bayesian state estimation
  • Implement and apply an extended Kalman filter (EKF), and to select appropriate parameters for it
  • Implement and apply a PID controller for state control, and to fine tune its parameters
  • Understand and explain the principles of visual motion estimation and 3D mapping

Prerequisite

None.

Instructors

  • Jürgen Sturm
  • Daniel Cremers
  • Christian Kerl

Editor

Technische Universität München

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