Software of TTool: a supervised AI-assisted Visual Pose Detector for AR Wood-working

TTool is developed at the Laboratory for Timber Construction (director: Prof.Yves Weinand) with the support of the EPFL Center for Imaging and the SCITAS, at EPFL, Lausanne, Switzerland. The project is part of the Augmented Carpentry Research. It is an open-source AI-powered and supervised 6DoF detector for monocular camera. It is developed in C++ and for UNIX systems to allow accurate end-effectors detection during wood-working operations such as cutting, drilling, sawing and screwing with multiple tools. This is a fundamental component of any subtractive AR fabrication system since you can for instance, calculate and give users feedback on the correct orientation and depth to start and finish a hole or a cut.

🖧 TTool is a AI-6DoF pose detector that recognizes automatically tools and allows the user to input an initial pose via an AR manipulator. The pose is then refined by a modified version of SLET (checkout our changelog) and visualized as a projection onto the camera feed.

↳ TTool can be imported as a C++ API in a third project or used as an executable. It is tailored to our specific use case in timber carpentry but see the Caveats section below to adapt it to your use case.