Real-Time On-the-Fly Motion Planning for Urban Air Mobility via Updating Tree Data of Sampling-Based Algorithms Using Neural Network Inference

Keyphrases

• Urban Air Mobility 100%
• Motion Planning 100%
• Sampling Algorithm 100%
• Tree-structured Data 100%
• Neural Network Inference 100%
• Snapping 66%
• Policy Networks 66%
• Neural Network 33%
• Computation Time 33%
• Replanning 33%
• Recurrent Neural Network 33%
• Coupling Method 33%
• Reinforcement Learning Algorithm 33%
• Learning Algorithm 33%
• Generation Algorithm 33%
• Trajectory Planning 33%
• Network Applications 33%
• Trajectory Optimization 33%
• Goal Location 33%
• Urban Airspace 33%
• Mobility Application 33%
• Geofence 33%
• Decoupling Method 33%
• Minimal Time 33%
• Generative Adversarial Imitation Learning 33%
• Problem of Motion 33%
• Online Trajectory Generation 33%
• Landing Position 33%

Computer Science

• Motion Planning 100%
• Urban Air Mobility 100%
• Data Tree 100%
• Network Inference 100%
• Neural Network 100%
• Recurrent Neural Network 66%
• Trajectory Generation 33%
• Reinforcement Learning 33%
• Computation Time 33%
• Learning Algorithm 33%