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Robotics, Vision and Control

Fundamental algorithms in MATLAB: Third Edition

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2: Representing Position & Orientation

A fundamental requirement in robotics and computer vision is to represent the position and orientation of objects in an environment. Such objects include robots, cameras, workpieces, obstacles and paths. Position and orientation together is referred to as pose.

This chapter covers position, orientation and pose in 2D:

  • Points in 2D space
  • 2D coordinate frames
  • Representing orientation in 2D using angles, orthonormal rotation matrices and matrix exponentials
  • Representing pose in 2D using homogeneous transformation matrices and twists

and position, orientation and pose in 3D:

  • Points in 3D space
  • 3D coordinate frames
  • Representing orientation in 3D using orthonormal rotation matrices, Euler angles, roll-pitch-yaw angles, unit-quaternions, matrix exponentials
  • Representing pose in 3D using homogeneous transformation matrices and twists

as well as an introduction to configuration space.


Gimbal lock


Quaternions


Videos


Misc


Lie groups


Software

  • manif, Lie theory library for state estimation (C++ and Python)
  • tf2, coordinate frame transforms in ROS
  • Sophus, Lie groups for 2D and 3D geometry in C++

These links are kept in one place for every edition and checked monthly. Resources for every chapter.