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ADVANCED ROBOTIC VISION

Syllabus

Elements of visual perception. Image Sampling and Quantization. Tools for Image Processing and Analysis. Image Formation: Camera Models, Calibration, Single view geometry, Multiple view geometry, Epipolar geometry, Feature extraction. Position and Orientation: Feature based alignment, Pose estimation. Time varying pose and trajectories. Estimation of 3‐D structures from 2‐D images. Visual Odometry (VO): Semi‐direct VO, direct sparse odometry. Localization and Mapping: Initialization, Tracking, Mapping, geometric Simultaneous Localisation and Mapping (SLAM) formulations. Sensor combinations for 3D object reconstruction (Inertial Measurement Unit ‐ IMU, RGB‐Depth). 3D scanning systems. Recognition and Interpretation: Object detection, Instance recognition, Category recognition, Context and Scene understanding. Robotic vision toward position, orientation, and velocity estimation. Vision guided robotic systems, trajectory planning for pick‐and‐place tasks. Robotic vision in Industrial Applications: cutting and shaping, inspection and sorting, palletization and primary packaging, etc. AI algorithms in robotic vision.

Learning Outcomes

The aim of the course is to familiarize students with the basic robotic vision system tools, with an emphasis on studying and analyzing three-dimensional information and extracting information about the static and dynamic characteristics of robotic workspace. Upon successful completion of the course, students will be able to:

  • Understand tools of computational visual perception,
  • Handle tools for image processing and analysis,
  • Analyze aspects of two-dimensional and three-dimensional geometry as well as relevant geometric transformations,
  • Design and apply robotic vision systems for the estimation of the position and orientation of robotic mechanisms,
  • Design and apply robotic vision systems for representing three-dimensional objects,
  • Understand the principles of three-dimensional scanning,
  • Design and implement algorithms for robotic task through computer vision tools,
  • Apply tools of artificial intelligence to robotic vision applications, and
  • Apply the above knowledge in industrial applications.

For the ouline of the course press here.

STUDIES: