@inproceedings{ChavezBermudezCruzCastanonRuchayetal.2022,
  author    = {Chavez Bermudez, Victor Francisco and Cruz Castanon, Victor Fernando and Ruchay, Marco and Wollert, J{\"o}rg},
  title     = {Rapid prototyping framework for automation applications based on IO-Link},
  series = {Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkr{\"a}ftemangel},
  booktitle = {Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkr{\"a}ftemangel},
  editor    = {Leipzig, Hochschule f{\"u}r Technik, Wirtschaft und Kultur},
  address   = {Leipzig},
  isbn      = {978-3-910103-00-9},
  doi       = {10.33968/2022.28},
  pages     = {8 Seiten},
  year      = {2022},
  abstract  = {The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.},
  language  = {en}
}
@article{SchulteTiggesFoersterNikolovskietal.2022,
  author    = {Schulte-Tigges, Joschua and F{\"o}rster, Marco and Nikolovski, Gjorgji and Reke, Michael and Ferrein, Alexander and Kaszner, Daniel and Matheis, Dominik and Walter, Thomas},
  title     = {Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments},
  series = {Sensors},
  volume    = {22},
  journal   = {Sensors},
  number    = {19},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s22197146},
  pages     = {20 Seiten},
  year      = {2022},
  abstract  = {Abstract In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.},
  language  = {en}
}