In this project we develop an intelligent belay system for sports climbing that combines outstanding and absolutely reliable mechanical functionality with smart assistance and monitoring functions. This electromechanical belay system not only prevents potentially serious accidents by automatically braking the rope in the event of a fall, but can also detect operating errors via an intelligent sensor system and report them back to the belaying climber. At the heart of the system is a mechanical semi-automatic device which, independently of the power supply and electronics, brakes or stops the rope if too much rope passes through too quickly. The sensor system measures the speed at which the rope passes through and the movement of the belay device. An intelligent classification process can use the measured data to differentiate between a fall and a rapid rope release. Machine learning methods are used for this purpose.
Project partner : Edelrid GmbH, Isny
Funding: BMWK 05/2019 – 10/2022
Publications
News
Preprint published: IMUDiffusion by Michael Munz
16. December 2024
We are very happy that we could now publish a new pre-print publication with the title “IMUDiffusion: A Diffusion Model for Multivariate Time Series Synthetisation for Inertial Motion Capturing Systems” on arxiv here: https://arxiv.org/pdf/2411.02954 . The paper describes a new method for the synthetisation of time-series data like Inertial Motion Capturing Systems, which is based on a diffusion model.
The paper is currently under review in a peer-review journal on AI methods.
Poster at VerticalPro 2024 by Michael Munz
21. November 2024
We are happy to show our latest research from the project SafeClimb at the VericalPro 2024!
Related Publications
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