Autonomous Drone

CLIENT

MultiRotorResearch

We use End-2-End artificial intelligence to train computers human flying behavior to make drones avoid obstacles in real-time in even the most difficult situations.

Using human flying behavior our drone is more autonomous than competitors!

At Multi-rotor research, we strive to achieve fully autonomous flight through a diverse set of scenarios using a new innovative approach called End-2-End navigation. Instead of the competition that is separating tasks of autonomous flight into separate hand-coded subsystems. We use one single Artificial Intelligence model which can directly correlate image data to flight controls. As a result, the system is more coherent and flexible in finding solutions in the most complex scenarios.

CNN based ML path planning

Our system uses a single CNN model that predicts directions that the drone needs to follow. We use keras and Python to run our custom designed model on the edge using a jetson nano mounted on the drone. Our drone is a hexacopter design making it able to carry large payloads. Using a ZED 2 stereo vision camera our AI is capable to see depth to make better predictions.

Delta drone gang

On this project multiple deltas worked coming from all competences of FHICT. Designers worked on the buisniss image and dashboard, programmers worked on the ai system and dashboard backend and buisniss worked on validating the buisniss case.