Embedded decision making for UAV missions
Sara Zermani, Catherine Dezan, Reinhardt Euler · 2017
The aim of this paper is to propose an embedded Decision Making module for autonomous Unmanned Aerial Vehicle (UAV, commonly known as drone) missions, based on Influence Diagrams. The module allows the choice of the adequate recovery action in the case of failure scenarios. We jointly show the application of this approach to a real drone mission. We also propose embedded hardware and software implementations for adaptive, online and real-time Decision Making, which are demonstrated on a Hybrid CPU/FPGA Zynq platform.