This course teaches students the basic concepts and techniques used in the field of visual environment perception for mobile robots. Within the lecture we will review fundamental techniques and present "state of the art" solutions. Although the presented techniques are generally usable, the course will focus on field robotics for autonomous driving.

We will discuss:

• Camera geometry
  • Target based calibration
  • Numerical optimization
• Stereo Cameras
  • Multi View geometry
  • Stereo rectification
  • Stereo Matching
• Optical flow
  • Optical flow model
  • Dense and sparse methods
• Visuelle odometry
  • Lie groups and rotation matrices
  • Stereo odometry
  • Monocular  odometrie
• SLAM
  • Kalman Filter
  • PTAM
  • DTAM

Detailed course information will be presented in a preliminary discussion in the first lecture on the 4th Oct. 2018. Pls note that there are no lectures on the 20th Dec. and 10th Jan. Furthermore, all informations are available in the corresponding TUWEL course.

ECTS-Breakdown: 75h:

• 15h Lectures (5*3h)
• 45h Programming exercise (3*13h )
• 13h Test preparation
• 2h   Test

Students have to solve three programming examples which will be graded during a personal delivery.

Requirements:

• basic programming skills
• basic knowledge of linear algebra and analysis
• basic knowledge in image processing