Tackling different aspects of drone services utilizing technologies from cross-sectional industries

Enabling autonomous and Beyond Visual Line of Sight (BVLOS) operation of Unmanned Aerial Vehicles (UAVs) in the Very Low Level (VLL) airspace requires further advancement of technologies such as sensing the environment or secure and reliable communication. This paper addresses these challenges by presenting solutions developed within the project Airborne Data Collection on Resilient System Architectures (ADACORSA). Here, findings from cross-sectional areas such as the automotive industry are being further enhanced to fulfill the demands of aviation, in particular for use in the UAV domain. The developed technologies include an advanced Ethernet-based deterministic network for reliable onboard communication, a multi-sensor architecture for sensing the spatial environment as well as a multi-link communication gateway that provides reliable communication to the ground and a secure handover architecture.ADACORSA has received funding from the ECSEL Joint Undertaking (JU) and National Authorities under grant agreement No 876019. Follow www.adacorsa.eu for more informatio

Multisensor Avionics Architecture for BVLOS Drone Services

This ADACORSA demonstrator focuses on the implementation of a failoperational avionics architecture combining Commercial Off-The-Shelf (COTS) elements from the automotive, the aerospace and the artificial intelligence world. A collaborative sensor setup (Time-of-Flight camera and FMCW RADAR from Infineon Technologies, stereo camera, LiDAR, IMU and GPS) allows to test heterogeneous sensor fusion solutions. A Tricore Architecture on AURIXTM Microcontroller supports the execution of safety supervision tasks as well as data fusion. A powerful embedded computer platform (NVIDIA Jetson Nano) accelerates AI algorithms performance and data processing. Furthermore, an FPGA enables power optimization of Artificial Neural Networks. Finally, a Pixhawk open-source flight controller ensures stabilization during normal flight operation and provides computer vision software modules allowing further processing of the captured, filtered and optimized environmental data. This paper shows various hardware and software implementations highlighting their emerging application within BVLOS drone services.EU-funded project ADACORSAECSEL Joint Undertaking (JU) under grant agreement No 876019European Union’s Horizon 2020German Federal Ministry of Education and Researc

AirLoop: A Simulation Framework for Testing of UAV Services

This work was supported in part by the European Union (EU)-Funded Project Airborne Data Collection on Resilient System Architectures (ADACORSA) (www.adacorsa.eu) through the Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking (JU) support from the European Union’s Horizon 2020 Research and Innovation Programme and Germany, The Netherlands, Austria, Romania, France, Sweden, Cyprus, Greece, Lithuania, Portugal, Italy, Finland, Turkey, under Agreement 876019; in part by the Spanish Ministerio de Economía y Competitividad under Project TED2021-129949A-I00; and in part by the Junta de Andalucía under Project P20_00265.Sensor fusion is a critical aspect in autonomous drone navigation as several tasks, such as object detection and self-pose estimation, require combining information from heterogeneous sources. The performance of these solutions depends on several factors, such as the characteristics of the sensors and the environment, as well as the computing platforms, which can heavily impact their accuracy and response time. Carrying out such performance evaluations through real flight tests can be a resource-demanding, time- consuming, and, at times, risky process, which is why researchers often rely on simulation environments for testing and validating sensor fusion algorithms. The simulation environment should provide photorealistic environmental features, as well as a comprehensive set of sensors, in order to allow to test the most extensive set of sensor fusion algorithms. This paper presents AirLoop, an AirSim-based flight simulator for Hardware- in-the-Loop and Software-in-the-Loop algorithm testing and validation. AirLoop extends the sensor setup provided by AirSim with an FMCW RADAR sensor simulation, which has been evaluated based on the Infineon Technologies BGT60TR13C RADAR. Furthermore, this work provides several Software-in-the- Loop (SITL) and Hardware-in-the-Loop (HITL) demonstrations, including interfacing with the Pixhawk 2 flight controller and an extensive evaluation of the communication of the engine with the NVIDIA Jetson Nano, which has been evaluated in various use cases, including dataset creation, object detection, Path Planning, and Simultaneous Localization and Mapping (SLAM).European Union (EU)-Funded Project Airborne Data Collection on Resilient System Architectures(ADACORSA)European Commission 876019Spanish Government TED2021-129949A-I00Junta de Andalucia P20_0026