A5039673590- Robotic Path Planning Algorithms
- Air Traffic Management and Optimization
- Autonomous Vehicle Technology and Safety
Cranfield University
2021-2024
In this study, we consider the problem of motion planning for urban air mobility applications to generate a minimal snap trajectory and that cost time reach goal location in presence dynamic geo-fences uncertainties airspace. We have developed two separate approaches because designing an algorithm individually each objective yields better performance. The first approach propose is decoupled method includes policy network based on recurrent neural reinforcement learning algorithm, then...
Urban air mobility provides an enabling technology towards on-demand and flexible operations for passenger cargo transportation in metropolitan areas. Electric vertical-takeoff landing (eVTOL) concept is a potential candidate urban platform because of its lower carbon emissions, noise generations potentially operational costs. However, such model subject to numerous complicated environmental design factors including buildings, dynamic obstacles micro-weather patterns. In addition,...
In this study, we consider the problem of motion planning for urban air mobility applications to generate minimal snap trajectory and that cost time reach goal location in presence dynamic geo-fences uncertainties airspace. We have developed two separate approaches because designing an algorithm individually each objective yields better performance. The first approach proposed is a decoupled method includes policy network based on recurrent neural reinforcement learning algorithm, then...