Project Description Our team will start by gaining proficiency in MATLAB®, Simulink®, UAV Toolbox, and other necessary resources and background material provided to us. Next, we will configure a simulation scenario resembling a cuboid with multiple stationary obstacles, simulating an urban setting, utilizing a UAV Toolbox. We will proceed to create a 3D path-planning algorithm for drone flight that ensures collision-free navigation, taking advantage of the path-planning resources designed for a single drone. To initiate this process, we will utilize the ground truth data from simulated drones. Finally, we will evaluate the performance of the algorithm in a cuboid scenario environment involving multiple drone flights.

Motivation

Path planning within the realm of Urban Air Mobility (UAM), encompassing air taxis and drone deliveries, presents a pivotal challenge for the transportation sector. With the exponential growth of UAM, the need for highly efficient and optimized path-planning algorithms is poised to surge. According to the Grand View Research Report, the drone delivery market is projected to reach an estimated $583.51 billion by 2023, while Morgan Stanley predicts the air taxi market will soar to $1.5 trillion by 2040. The development of an efficient path-planning system for UAM has the potential to revolutionize urban transportation, rendering cities more livable and sustainable. Such an algorithm will be instrumental in orchestrating collision-free paths for multiple drones operating within the same environment, all while minimizing time and cost. This project represents a distinctive opportunity to wield cutting-edge technology in addressing the intricate challenges of path planning in UAM, thereby leaving an indelible mark on the future of transportation and logistics.

Scope:

• Skill Enhancement: Commence the project by enhancing proficiency in MATLAB®, Simulink®, UAV Toolbox, and other resources provided in the background materials

• Scenario Simulation: Configure a simulated urban environment within a cuboid scenario, serving as a realistic testing ground for our path planning and collision avoidance system

• Single-Drone Path Planning: Develop a 3D path-planning algorithm for single drone flights, ensuring collision-free navigation while optimizing time and cost

• Centralized Tracking: Explore and implement centralized tracking techniques to ensure seamless, collision-free guidance for all drones

• Performance Evaluation: Rigorous testing of the developed algorithm in the cuboid scenario environment with multiple drone flights; including performance metrics, collision avoidance, efficiency, and cost-effectiveness

Roles