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cs.RO2025
Learning Probabilistic Obstacle Spaces from Data-driven Uncertainty using Neural Networks
Jun Xiang, Jun Chen
Identifying the obstacle space is crucial for path planning. However, generating an accurate obstacle space remains a significant challenge due to various sources of uncertainty, i…
cs.RO2024
Transformer-based Heuristic for Advanced Air Mobility Planning
Jun Xiang, Jun Chen
Safety is extremely important for urban flights of autonomous Unmanned Aerial Vehicles (UAVs). Risk-aware path planning is one of the most effective methods to guarantee the safety…
cs.RO2024
Landing Trajectory Prediction for UAS Based on Generative Adversarial Network
Jun Xiang, Drake Essick, Luiz Gonzalez Bautista +2
Models for trajectory prediction are an essential component of many advanced air mobility studies. These models help aircraft detect conflict and plan avoidance maneuvers, which is…