Session type: Talk (15 minutes)
Track: Scientific Applications
Abstract as a tweet: Introduction to 3D transformations in Python illustrated with problems in robotics
Category [Scientific Applications]: Robotics & IoT
Expected audience expertise (Domain): none
Expected audience expertise (Python): some
Talk submissions only: Would you be prepared to do a poster as fallback? - yes
Public link to supporting material: --
Project Homepage / Git: https://github.com/dfki-ric/pytransform3d
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.
This talk focuses on rotation and translation, that is, rigid transformations, in three dimensions. There are various representations of these. We often combine several software components with different conventions. Furthermore, we usually combine multiple transformations that form complex graphs of transformations, and we are often interested in transformations that are not directly available, but can be computed from a combination of multiple transformations. Both problems can be handled with pytransform3d, a Python library for transformations in three dimensions.
pytransform3d offers...
- operations for most common representations of rotation / orientation and translation / position
- conversions between those representations
- clear documentation of conventions
- tight coupling with matplotlib to quickly visualize (or animate) transformations
- the TransformManager which organizes complex chains of transformations
- the UrdfTransformManager which is able to load transformations from URDF files
- a matplotlib-like interface to Open3D’s visualizer to display geometries and transformations
I will present several features of the library in this talk and I will use examples from robotics for illustration, for example,
- imitation learning - learning robotic motion from human demonstration
- kinematics - translation of a human hand motion to a robotic hand
- collision detection - between a robot arm and it's environment
- state estimation - estimation of a robot's location and its uncertainty
There are several pitfalls that we will discuss as well.
You can build the slides with texlive in the subdirectory talk:
pdflatex slides.tex
biber slides
pdflatex slides.texI recommend to use Okular to view the slides because I use the multimedia package to include videos.