Data fusion for sUAS navigation systems using reservoir computing

ResCon will commercialize revolutionary machine-learning algorithms for fusing data from multiple sensors on small unmanned aerial systems (sUAS) to greatly improve navigation in GPS-denied and uncertain environments experienced during disaster and search and rescue missions.  ResCon’s data-fusion algorithm addresses an unmet need that is a result of the growing complexity of sensors on sUAS that are used for navigation and situational awareness.  ResCon's architecture is platform and sensor agnostic and can be integrated with any drone with one-time engineering setup.  Furthermore, the algorithm does not need extensive computational resources or training data and is 1,000 to 1,000,000 times faster than Deep Learning approaches.  This allows for implementation on edge devices and provides continuous learning and retraining during flight to adapt to a changing environment.