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In this project, I developed the estimation portion of my controller for the drone in the Udacity CPP simulator. My simulated quad is now able to fly with my estimator and my custom controller (from project 3).)
In this project, I applied 3D Notion Planning techniques to implement a drone agent capable of plan and execute missions in a complex urban environment.
Hybrid Transformer based Multi-agent Reinforcement Learning (HTransRL) is for drone coordination in air corridors, addressing the challenges of dynamic dimensions and types of state inputs, which cannot addressed by the traditional MARL.
Extension for MATSim to allow for the inclusion of aerial passenger-carrying vehicles, i.e. a station- and network-bound transport mode that requires station access and egress trips with conventional ground-based modes.