Trajectory Prediction

Trajectory prediction focuses on forecasting the future movement of objects, particularly crucial for autonomous systems like self-driving cars and robots. Current research emphasizes improving prediction accuracy and robustness, especially in complex, uncertain environments, using diverse model architectures such as transformers, graph neural networks, and diffusion models, often incorporating multimodal data (e.g., images, LiDAR, maps) and addressing challenges like uncertainty quantification and out-of-distribution generalization. This field is vital for enhancing the safety and efficiency of autonomous systems and has significant implications for various applications, including robotics, traffic management, and assistive technologies.