Modeling Unmanned Aerial Vehicles in an Autonomous World Assaf Mozes, CDA Group Manager, Systematics

Unmanned systems are gaining momentum in a wide variety of fields and can now be found in many uses at sea, in the air and on land. These systems make it possible to perform difficult and complicated tasks, while reducing risk levels and increasing work comfort.
This lecture will begin with an introduction to the Model-Based Design process and the Unmanned Aerial Vehicle (UAV) solution, which enables the design, testing, and deployment of algorithms for unmanned aerial systems and their expansion using Aerospace capabilities.
This solution allows us to quickly model the UAV system and focus on developing its autonomy algorithms, analyzing its behavior in a physical environment, and even testing the system on different hardware.

During the lecture we will review the capabilities that enable the UAV system to operate and behave autonomously:

Platform – a single development environment that allows us to model the system itself
Sense – how to model and symbolize different sensors and perform a fusion of the information obtained from them (Sensor Fusion).
Perceive – a process of classification and decoding that gives meaning to the environment (Deep Learning).
Route planning (Plan) – the world of navigation, mapping the work area and planning a route for the system’s traffic.
Route Control – Algorithms that verify that the system is indeed operating according to the planned route.
Connectivity – Creating code and deploying it on hardware and running the algorithms and models on physical simulators.