ASTRI’s work in smart mobility is about applying artificial intelligence, big-data analytics, video analytics and graph theory to solve traffic problems. They can be applied to multiple application domains, such as robotics and transportation.
As the autonomous vehicle industry racing from zero to warp speed, it calls for technology innovations in every aspect of this field. For automated guided vehicle (AGV), one type of autonomous vehicles, its global market alone is projected to be US$2.68B by 2022.
An intelligent platform for scheduling and routing for AGV is developed to address the technical challenges in this area. In an environment of hundreds or even thousands of vehicles, the technical challenges include looking for the most efficient routes for all vehicles and the optimising the assignment of vehicles to perform their tasks. Issues of scalability, avoiding traffic jams, detecting obstacles ahead etc. must be addressed. In this project, deep learning is incorporated to improve on dynamic route optimization, large-scale vehicle planning and task scheduling. ASTRI’s initial application will be to AGVs for distribution centers.