Perception Algorithm

Perception algorithms are crucial for autonomous systems, aiming to accurately interpret sensor data (e.g., from cameras, lidar, radar) to understand the environment. Current research emphasizes improving robustness in challenging conditions (adverse weather, low light) through data augmentation and adaptive thresholding, as well as developing efficient and modular architectures like hierarchical Bird's-Eye-View (BEV) models and collaborative perception strategies. This work is vital for advancing the safety and reliability of autonomous vehicles, robots, and other applications requiring real-time environmental awareness, particularly by addressing limitations in current perception models and improving their ability to handle uncertainty.