Description
Rigid transformation in 3D are complicated due to the multitude of different conventions and because they often form complex graphs that are difficult to manage. In this talk I will give a brief introduction to the topic and present the library pytransform3d as a set of tools that can help you to tame the complexity. Throughout the talk I will use examples from robotics (imitation learning, collision detection, state estimation, kinematics) to motivate the discussed features, even though presented solutions are useful beyond robotics.